Publications

Displaying 1 - 100 of 1147
  • Bauer, B. L. M. (in press). Finite verb + infinite + object in later Latin: Early brace constructions? In Latin vulgaire – latin tardif XII.
  • Bruggeman, L., Yu, J., & Cutler, A. (in press). Listener adjustment of stress cue use to fit language vocabulary structure. In Proceedings of Speech Prosody 2022.

    Abstract

    In lexical stress languages, phonemically identical syllables can differ suprasegmentally (in duration, amplitude, F0). Such stress cues allow listeners to speed spoken-word recognition by rejecting mismatching competitors (e.g., unstressed set- in settee rules out stressed set- in setting, setter, settle). Such processing effects have indeed been observed in Spanish, Dutch and German, but English listeners are known to largely ignore stress cues. Dutch and German listeners even outdo English listeners in distinguishing stressed versus unstressed English syllables. This has been attributed to the relative frequency across the stress languages of unstressed syllables with full vowels; in English most unstressed syllables contain schwa, instead, and stress cues on full vowels are thus least often informative in this language. If only informativeness matters, would English listeners who encounter situations where such cues would pay off for them (e.g., learning one of those other stress languages) then shift to using stress cues? Likewise, would stress cue users with English as L2, if mainly using English, shift away from using the cues in English? Here we report tests of these two questions, with each receiving a yes answer. We propose that English listeners’ disregard of stress cues is purely pragmatic.
  • Galke, L., & Scherp, A. (in press). Bag-of-words vs. graph vs. sequence in text classification: Questioning the necessity of text-graphs and the surprising strength of a wide MLP. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics.
  • Hintz, F., Voeten, C. C., McQueen, J. M., & Meyer, A. S. (in press). Quantifying the relationships between linguistic experience, general cognitive skills and linguistic processing skills. In Proceedings of the 44th Annual Conference of the Cognitive Science Society (CogSci 2022). Toronto: Cognitive Science Society.

    Abstract

    Humans differ greatly in their ability to use language. Contemporary psycholinguistic theories assume that individual differences in language skills arise from variability in linguistic experience and in general cognitive skills. While much previous research has tested the involvement of select verbal and non-verbal variables in select domains of linguistic processing, comprehensive characterizations of the relationships among the skills underlying language use are rare. We contribute to such a research program by re-analyzing a publicly available set of data from 112 young adults tested on 35 behavioral tests. The tests assessed nine key constructs reflecting linguistic processing skills, linguistic experience and general cognitive skills. Correlation and hierarchical clustering analyses of the test scores showed that most of the tests assumed to measure the same construct correlated moderately to strongly and largely clustered together. Furthermore, the results suggest important roles of processing speed in comprehension, and of linguistic experience in production.
  • Coopmans, C. W., De Hoop, H., Kaushik, K., Hagoort, P., & Martin, A. E. (2021). Structure-(in)dependent interpretation of phrases in humans and LSTMs. In Proceedings of the Society for Computation in Linguistics (SCiL 2021) (pp. 459-463).

    Abstract

    In this study, we compared the performance of a long short-term memory (LSTM) neural network to the behavior of human participants on a language task that requires hierarchically structured knowledge. We show that humans interpret ambiguous noun phrases, such as second blue ball, in line with their hierarchical constituent structure. LSTMs, instead, only do so after unambiguous training, and they do not systematically generalize to novel items. Overall, the results of our simulations indicate that a model can behave hierarchically without relying on hierarchical constituent structure.
  • Cutler, A., Aslin, R. N., Gervain, J., & Nespor, M. (Eds.). (2021). Special issue in honor of Jacques Mehler, Cognition's founding editor [Special Issue]. Cognition, 213.
  • Evans, N., Levinson, S. C., & Sterelny, K. (Eds.). (2021). Thematic issue on evolution of kinship systems [Special Issue]. Biological theory, 16.
  • Eviatar, Z., & Huettig, F. (Eds.). (2021). Literacy and writing systems [Special Issue]. Journal of Cultural Cognitive Science.
  • Galke, L., Seidlmayer, E., Lüdemann, G., Langnickel, L., Melnychuk, T., Förstner, K. U., Tochtermann, K., & Schultz, C. (2021). COVID-19++: A citation-aware Covid-19 dataset for the analysis of research dynamics. In Y. Chen, H. Ludwig, Y. Tu, U. Fayyad, X. Zhu, X. Hu, S. Byna, X. Liu, J. Zhang, S. Pan, V. Papalexakis, J. Wang, A. Cuzzocrea, & C. Ordonez (Eds.), Proceedings of the 2021 IEEE International Conference on Big Data (pp. 4350-4355). Piscataway, NJ: IEEE.

    Abstract

    COVID-19 research datasets are crucial for analyzing research dynamics. Most collections of COVID-19 research items do not to include cited works and do not have annotations from a controlled vocabulary. Starting with ZB MED KE data on COVID-19, which comprises CORD-19, we assemble a new dataset that includes cited work and MeSH annotations for all records. Furthermore, we conduct experiments on the analysis of research dynamics, in which we investigate predicting links in a co-annotation graph created on the basis of the new dataset. Surprisingly, we find that simple heuristic methods are better at predicting future links than more sophisticated approaches such as graph neural networks.
  • Galke, L., Franke, B., Zielke, T., & Scherp, A. (2021). Lifelong learning of graph neural networks for open-world node classification. In Proceedings of the 2021 International Joint Conference on Neural Networks (IJCNN). Piscataway, NJ: IEEE. doi:10.1109/IJCNN52387.2021.9533412.

    Abstract

    Graph neural networks (GNNs) have emerged as the standard method for numerous tasks on graph-structured data such as node classification. However, real-world graphs are often evolving over time and even new classes may arise. We model these challenges as an instance of lifelong learning, in which a learner faces a sequence of tasks and may take over knowledge acquired in past tasks. Such knowledge may be stored explicitly as historic data or implicitly within model parameters. In this work, we systematically analyze the influence of implicit and explicit knowledge. Therefore, we present an incremental training method for lifelong learning on graphs and introduce a new measure based on k-neighborhood time differences to address variances in the historic data. We apply our training method to five representative GNN architectures and evaluate them on three new lifelong node classification datasets. Our results show that no more than 50% of the GNN's receptive field is necessary to retain at least 95% accuracy compared to training over the complete history of the graph data. Furthermore, our experiments confirm that implicit knowledge becomes more important when fewer explicit knowledge is available.
  • Greenfield, M. D., Honing, H., Kotz, S. A., & Ravignani, A. (Eds.). (2021). Synchrony and rhythm interaction: From the brain to behavioural ecology [Special Issue]. Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences, 376.
  • Hintz, F., Voeten, C. C., McQueen, J. M., & Scharenborg, O. (2021). The effects of onset and offset masking on the time course of non-native spoken-word recognition in noise. In T. Fitch, C. Lamm, H. Leder, & K. Teßmar-Raible (Eds.), Proceedings of the 43rd Annual Conference of the Cognitive Science Society (CogSci 2021) (pp. 133-139). Vienna: Cognitive Science Society.

    Abstract

    Using the visual-word paradigm, the present study investigated the effects of word onset and offset masking on the time course of non-native spoken-word recognition in the presence of background noise. In two experiments, Dutch non-native listeners heard English target words, preceded by carrier sentences that were noise-free (Experiment 1) or contained intermittent noise (Experiment 2). Target words were either onset- or offset-masked or not masked at all. Results showed that onset masking delayed target word recognition more than offset masking did, suggesting that – similar to natives – non-native listeners strongly rely on word onset information during word recognition in noise.

    Additional information

    Link to Preprint on BioRxiv
  • Karadöller, D. Z., Sumer, B., Ünal, E., & Ozyurek, A. (2021). Spatial language use predicts spatial memory of children: Evidence from sign, speech, and speech-plus-gesture. In T. Fitch, C. Lamm, H. Leder, & K. Teßmar-Raible (Eds.), Proceedings of the 43rd Annual Conference of the Cognitive Science Society (CogSci 2021) (pp. 672-678). Vienna: Cognitive Science Society.

    Abstract

    There is a strong relation between children’s exposure to spatial terms and their later memory accuracy. In the current study, we tested whether the production of spatial terms by children themselves predicts memory accuracy and whether and how language modality of these encodings modulates memory accuracy differently. Hearing child speakers of Turkish and deaf child signers of Turkish Sign Language described pictures of objects in various spatial relations to each other and later tested for their memory accuracy of these pictures in a surprise memory task. We found that having described the spatial relation between the objects predicted better memory accuracy. However, the modality of these descriptions in sign, speech, or speech-plus-gesture did not reveal differences in memory accuracy. We discuss the implications of these findings for the relation between spatial language, memory, and the modality of encoding.
  • Levshina, N., & Moran, S. (Eds.). (2021). Efficiency in human languages: Corpus evidence for universal principles [Special Issue]. Linguistics Vanguard, 7(s3).
  • Mamus, E., Speed, L. J., Ozyurek, A., & Majid, A. (2021). Sensory modality of input influences encoding of motion events in speech but not co-speech gestures. In T. Fitch, C. Lamm, H. Leder, & K. Teßmar-Raible (Eds.), Proceedings of the 43rd Annual Conference of the Cognitive Science Society (CogSci 2021) (pp. 376-382). Vienna: Cognitive Science Society.

    Abstract

    Visual and auditory channels have different affordances and this is mirrored in what information is available for linguistic encoding. The visual channel has high spatial acuity, whereas the auditory channel has better temporal acuity. These differences may lead to different conceptualizations of events and affect multimodal language production. Previous studies of motion events typically present visual input to elicit speech and gesture. The present study compared events presented as audio- only, visual-only, or multimodal (visual+audio) input and assessed speech and co-speech gesture for path and manner of motion in Turkish. Speakers with audio-only input mentioned path more and manner less in verbal descriptions, compared to speakers who had visual input. There was no difference in the type or frequency of gestures across conditions, and gestures were dominated by path-only gestures. This suggests that input modality influences speakers’ encoding of path and manner of motion events in speech, but not in co-speech gestures.
  • Mudd, K., Lutzenberger, H., De Vos, C., & De Boer, B. (2021). Social structure and lexical uniformity: A case study of gender differences in the Kata Kolok community. In T. Fitch, C. Lamm, H. Leder, & K. Teßmar-Raible (Eds.), Proceedings of the 43rd Annual Conference of the Cognitive Science Society (CogSci 2021) (pp. 2692-2698). Vienna: Cognitive Science Society.

    Abstract

    Language emergence is characterized by a high degree of lex- ical variation. It has been suggested that the speed at which lexical conventionalization occurs depends partially on social structure. In large communities, individuals receive input from many sources, creating a pressure for lexical convergence. In small, insular communities, individuals can remember id- iolects and share common ground with interlocuters, allow- ing these communities to retain a high degree of lexical vari- ation. We look at lexical variation in Kata Kolok, a sign lan- guage which emerged six generations ago in a Balinese vil- lage, where women tend to have more tightly-knit social net- works than men. We test if there are differing degrees of lexical uniformity between women and men by reanalyzing a picture description task in Kata Kolok. We find that women’s produc- tions exhibit less lexical uniformity than men’s. One possible explanation of this finding is that women’s more tightly-knit social networks allow for remembering idiolects, alleviating the pressure for lexical convergence, but social network data from the Kata Kolok community is needed to support this ex- planation.
  • Pouw, W., Wit, J., Bögels, S., Rasenberg, M., Milivojevic, B., & Ozyurek, A. (2021). Semantically related gestures move alike: Towards a distributional semantics of gesture kinematics. In V. G. Duffy (Ed.), Digital human modeling and applications in health, safety, ergonomics and risk management. human body, motion and behavior:12th International Conference, DHM 2021, Held as Part of the 23rd HCI International Conference, HCII 2021 (pp. 269-287). Berlin: Springer. doi:10.1007/978-3-030-77817-0_20.
  • Trujillo, J. P., Levinson, S. C., & Holler, J. (2021). Visual information in computer-mediated interaction matters: Investigating the association between the availability of gesture and turn transition timing in conversation. In M. Kurosu (Ed.), Human-Computer Interaction. Design and User Experience Case Studies. HCII 2021 (pp. 643-657). Cham: Springer. doi:10.1007/978-3-030-78468-3_44.

    Abstract

    Natural human interaction involves the fast-paced exchange of speaker turns. Crucially, if a next speaker waited with planning their turn until the current speaker was finished, language production models would predict much longer turn transition times than what we observe. Next speakers must therefore prepare their turn in parallel to listening. Visual signals likely play a role in this process, for example by helping the next speaker to process the ongoing utterance and thus prepare an appropriately-timed response. To understand how visual signals contribute to the timing of turn-taking, and to move beyond the mostly qualitative studies of gesture in conversation, we examined unconstrained, computer-mediated conversations between 20 pairs of participants while systematically manipulating speaker visibility. Using motion tracking and manual gesture annotation, we assessed 1) how visibility affected the timing of turn transitions, and 2) whether use of co-speech gestures and 3) the communicative kinematic features of these gestures were associated with changes in turn transition timing. We found that 1) decreased visibility was associated with less tightly timed turn transitions, and 2) the presence of gestures was associated with more tightly timed turn transitions across visibility conditions. Finally, 3) structural and salient kinematics contributed to gesture’s facilitatory effect on turn transition times. Our findings suggest that speaker visibility--and especially the presence and kinematic form of gestures--during conversation contributes to the temporal coordination of conversational turns in computer-mediated settings. Furthermore, our study demonstrates that it is possible to use naturalistic conversation and still obtain controlled results.
  • Vernes, S. C., Janik, V. M., Fitch, W. T., & Slater, P. J. B. (Eds.). (2021). Vocal learning in animals and humans [Special Issue]. Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences, 376.
  • Zhang, Y., Ding, R., Frassinelli, D., Tuomainen, J., Klavinskis-Whiting, S., & Vigliocco, G. (2021). Electrophysiological signatures of second language multimodal comprehension. In T. Fitch, C. Lamm, H. Leder, & K. Teßmar-Raible (Eds.), Proceedings of the 43rd Annual Conference of the Cognitive Science Society (CogSci 2021) (pp. 2971-2977). Vienna: Cognitive Science Society.

    Abstract

    Language is multimodal: non-linguistic cues, such as prosody, gestures and mouth movements, are always present in face-to- face communication and interact to support processing. In this paper, we ask whether and how multimodal cues affect L2 processing by recording EEG for highly proficient bilinguals when watching naturalistic materials. For each word, we quantified surprisal and the informativeness of prosody, gestures, and mouth movements. We found that each cue modulates the N400: prosodic accentuation, meaningful gestures, and informative mouth movements all reduce N400. Further, effects of meaningful gestures but not mouth informativeness are enhanced by prosodic accentuation, whereas effects of mouth are enhanced by meaningful gestures but reduced by beat gestures. Compared with L1, L2 participants benefit less from cues and their interactions, except for meaningful gestures and mouth movements. Thus, in real- world language comprehension, L2 comprehenders use multimodal cues just as L1 speakers albeit to a lesser extent.
  • Alhama, R. G., Rowland, C. F., & Kidd, E. (2020). Evaluating word embeddings for language acquisition. In E. Chersoni, C. Jacobs, Y. Oseki, L. Prévot, & E. Santus (Eds.), Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics (pp. 38-42). Stroudsburg, PA, USA: Association for Computational Linguistics (ACL).

    Abstract

    Continuous vector word representations (or word embeddings) have shown success in cap-turing semantic relations between words, as evidenced by evaluation against behavioral data of adult performance on semantic tasks (Pereira et al., 2016). Adult semantic knowl-edge is the endpoint of a language acquisition process; thus, a relevant question is whether these models can also capture emerging word representations of young language learners. However, the data for children’s semantic knowledge across development is scarce. In this paper, we propose to bridge this gap by using Age of Acquisition norms to evaluate word embeddings learnt from child-directed input. We present two methods that evaluate word embeddings in terms of (a) the semantic neighbourhood density of learnt words, and (b) con- vergence to adult word associations. We apply our methods to bag-of-words models, and find that (1) children acquire words with fewer semantic neighbours earlier, and (2) young learners only attend to very local context. These findings provide converging evidence for validity of our methods in understanding the prerequisite features for a distributional model of word learning.
  • Asano, Y., Yuan, C., Grohe, A.-K., Weber, A., Antoniou, M., & Cutler, A. (2020). Uptalk interpretation as a function of listening experience. In N. Minematsu, M. Kondo, T. Arai, & R. Hayashi (Eds.), Proceedings of Speech Prosody 2020 (pp. 735-739). Tokyo: ISCA. doi:10.21437/SpeechProsody.2020-150.

    Abstract

    The term “uptalk” describes utterance-final pitch rises that carry no sentence-structural information. Uptalk is usually dialectal or sociolectal, and Australian English (AusEng) is particularly known for this attribute. We ask here whether experience with an uptalk variety affects listeners’ ability to categorise rising pitch contours on the basis of the timing and height of their onset and offset. Listeners were two groups of English-speakers (AusEng, and American English), and three groups of listeners with L2 English: one group with Mandarin as L1 and experience of listening to AusEng, one with German as L1 and experience of listening to AusEng, and one with German as L1 but no AusEng experience. They heard nouns (e.g. flower, piano) in the framework “Got a NOUN”, each ending with a pitch rise artificially manipulated on three contrasts: low vs. high rise onset, low vs. high rise offset and early vs. late rise onset. Their task was to categorise the tokens as “question” or “statement”, and we analysed the effect of the pitch contrasts on their judgements. Only the native AusEng listeners were able to use the pitch contrasts systematically in making these categorisations.
  • De Boer, B., Thompson, B., Ravignani, A., & Boeckx, C. (2020). Analysis of mutation and fixation for language. In A. Ravignani, C. Barbieri, M. Flaherty, Y. Jadoul, E. Lattenkamp, H. Little, M. Martins, K. Mudd, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 13th International Conference (Evolang13) (pp. 56-58). Nijmegen: The Evolution of Language Conferences.
  • Doumas, L. A. A., Martin, A. E., & Hummel, J. E. (2020). Relation learning in a neurocomputational architecture supports cross-domain transfer. In S. Denison, M. Mack, Y. Xu, & B. C. Armstrong (Eds.), Proceedings of the 42nd Annual Virtual Meeting of the Cognitive Science Society (CogSci 2020) (pp. 932-937). Montreal, QB: Cognitive Science Society.

    Abstract

    Humans readily generalize, applying prior knowledge to novel situations and stimuli. Advances in machine learning have begun to approximate and even surpass human performance, but these systems struggle to generalize what they have learned to untrained situations. We present a model based on wellestablished neurocomputational principles that demonstrates human-level generalisation. This model is trained to play one video game (Breakout) and performs one-shot generalisation to a new game (Pong) with different characteristics. The model generalizes because it learns structured representations that are functionally symbolic (viz., a role-filler binding calculus) from unstructured training data. It does so without feedback, and without requiring that structured representations are specified a priori. Specifically, the model uses neural co-activation to discover which characteristics of the input are invariant and to learn relational predicates, and oscillatory regularities in network firing to bind predicates to arguments. To our knowledge, this is the first demonstration of human-like generalisation in a machine system that does not assume structured representa- tions to begin with.
  • Ergin, R., Raviv, L., Senghas, A., Padden, C., & Sandler, W. (2020). Community structure affects convergence on uniform word orders: Evidence from emerging sign languages. In A. Ravignani, C. Barbieri, M. Flaherty, Y. Jadoul, E. Lattenkamp, H. Little, M. Martins, K. Mudd, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 13th International Conference (Evolang13) (pp. 84-86). Nijmegen: The Evolution of Language Conferences.
  • Hashemzadeh, M., Kaufeld, G., White, M., Martin, A. E., & Fyshe, A. (2020). From language to language-ish: How brain-like is an LSTM representation of nonsensical language stimuli? In Findings of the Association for Computational Linguistics: EMNLP 2020 (pp. 645-655).

    Abstract

    The representations generated by many mod- els of language (word embeddings, recurrent neural networks and transformers) correlate to brain activity recorded while people read. However, these decoding results are usually based on the brain’s reaction to syntactically and semantically sound language stimuli. In this study, we asked: how does an LSTM (long short term memory) language model, trained (by and large) on semantically and syntac- tically intact language, represent a language sample with degraded semantic or syntactic information? Does the LSTM representation still resemble the brain’s reaction? We found that, even for some kinds of nonsensical lan- guage, there is a statistically significant rela- tionship between the brain’s activity and the representations of an LSTM. This indicates that, at least in some instances, LSTMs and the human brain handle nonsensical data similarly.
  • De Heer Kloots, M., Carlson, D., Garcia, M., Kotz, S., Lowry, A., Poli-Nardi, L., de Reus, K., Rubio-García, A., Sroka, M., Varola, M., & Ravignani, A. (2020). Rhythmic perception, production and interactivity in harbour and grey seals. In A. Ravignani, C. Barbieri, M. Flaherty, Y. Jadoul, E. Lattenkamp, H. Little, M. Martins, K. Mudd, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 13th International Conference (Evolang13) (pp. 59-62). Nijmegen: The Evolution of Language Conferences.
  • Hoeksema, N., Wiesmann, M., Kiliaan, A., Hagoort, P., & Vernes, S. C. (2020). Bats and the comparative neurobiology of vocal learning. In A. Ravignani, C. Barbieri, M. Flaherty, Y. Jadoul, E. Lattenkamp, H. Little, M. Martins, K. Mudd, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 13th International Conference (Evolang13) (pp. 165-167). Nijmegen: The Evolution of Language Conferences.
  • Hoeksema, N., Villanueva, S., Mengede, J., Salazar Casals, A., Rubio-García, A., Curcic-Blake, B., Vernes, S. C., & Ravignani, A. (2020). Neuroanatomy of the grey seal brain: Bringing pinnipeds into the neurobiological study of vocal learning. In A. Ravignani, C. Barbieri, M. Flaherty, Y. Jadoul, E. Lattenkamp, H. Little, M. Martins, K. Mudd, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 13th International Conference (Evolang13) (pp. 162-164). Nijmegen: The Evolution of Language Conferences.
  • Khoe, Y. H., Tsoukala, C., Kootstra, G. J., & Frank, S. L. (2020). Modeling cross-language structural priming in sentence production. In T. C. Stewart (Ed.), Proceedings of the 18th Annual Meeting of the International Conference on Cognitive Modeling (pp. 131-137). University Park, PA, USA: The Penn State Applied Cognitive Science Lab.

    Abstract

    A central question in the psycholinguistic study of multilingualism is how syntax is shared across languages. We implement a model to investigate whether error-based implicit learning can provide an account of cross-language structural priming. The model is based on the Dual-path model of sentence-production (Chang, 2002). We implement our model using the Bilingual version of Dual-path (Tsoukala, Frank, & Broersma, 2017). We answer two main questions: (1) Can structural priming of active and passive constructions occur between English and Spanish in a bilingual version of the Dual- path model? (2) Does cross-language priming differ quantitatively from within-language priming in this model? Our results show that cross-language priming does occur in the model. This finding adds to the viability of implicit learning as an account of structural priming in general and cross-language structural priming specifically. Furthermore, we find that the within-language priming effect is somewhat stronger than the cross-language effect. In the context of mixed results from behavioral studies, we interpret the latter finding as an indication that the difference between cross-language and within- language priming is small and difficult to detect statistically.
  • Lattenkamp, E. Z., Linnenschmidt, M., Mardus, E., Vernes, S. C., Wiegrebe, L., & Schutte, M. (2020). Impact of auditory feedback on bat vocal development. In A. Ravignani, C. Barbieri, M. Flaherty, Y. Jadoul, E. Lattenkamp, H. Little, M. Martins, K. Mudd, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 13th International Conference (Evolang13) (pp. 249-251). Nijmegen: The Evolution of Language Conferences.
  • Lei, L., Raviv, L., & Alday, P. M. (2020). Using spatial visualizations and real-world social networks to understand language evolution and change. In A. Ravignani, C. Barbieri, M. Flaherty, Y. Jadoul, E. Lattenkamp, H. Little, M. Martins, K. Mudd, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 13th International Conference (Evolang13) (pp. 252-254). Nijmegen: The Evolution of Language Conferences.
  • Levshina, N. (2020). How tight is your language? A semantic typology based on Mutual Information. In K. Evang, L. Kallmeyer, R. Ehren, S. Petitjean, E. Seyffarth, & D. Seddah (Eds.), Proceedings of the 19th International Workshop on Treebanks and Linguistic Theories (pp. 70-78). Düsseldorf, Germany: Association for Computational Linguistics. doi:10.18653/v1/2020.tlt-1.7.

    Abstract

    Languages differ in the degree of semantic flexibility of their syntactic roles. For example, Eng- lish and Indonesian are considered more flexible with regard to the semantics of subjects, whereas German and Japanese are less flexible. In Hawkins’ classification, more flexible lan- guages are said to have a loose fit, and less flexible ones are those that have a tight fit. This classification has been based on manual inspection of example sentences. The present paper proposes a new, quantitative approach to deriving the measures of looseness and tightness from corpora. We use corpora of online news from the Leipzig Corpora Collection in thirty typolog- ically and genealogically diverse languages and parse them syntactically with the help of the Universal Dependencies annotation software. Next, we compute Mutual Information scores for each language using the matrices of lexical lemmas and four syntactic dependencies (intransi- tive subjects, transitive subject, objects and obliques). The new approach allows us not only to reproduce the results of previous investigations, but also to extend the typology to new lan- guages. We also demonstrate that verb-final languages tend to have a tighter relationship be- tween lexemes and syntactic roles, which helps language users to recognize thematic roles early during comprehension.

    Additional information

    full text via ACL website
  • MacDonald, K., Räsänen, O., Casillas, M., & Warlaumont, A. S. (2020). Measuring prosodic predictability in children’s home language environments. In S. Denison, M. Mack, Y. Xu, & B. C. Armstrong (Eds.), Proceedings of the 42nd Annual Virtual Meeting of the Cognitive Science Society (CogSci 2020) (pp. 695-701). Montreal, QB: Cognitive Science Society.

    Abstract

    Children learn language from the speech in their home environment. Recent work shows that more infant-directed speech (IDS) leads to stronger lexical development. But what makes IDS a particularly useful learning signal? Here, we expand on an attention-based account first proposed by Räsänen et al. (2018): that prosodic modifications make IDS less predictable, and thus more interesting. First, we reproduce the critical finding from Räsänen et al.: that lab-recorded IDS pitch is less predictable compared to adult-directed speech (ADS). Next, we show that this result generalizes to the home language environment, finding that IDS in daylong recordings is also less predictable than ADS but that this pattern is much less robust than for IDS recorded in the lab. These results link experimental work on attention and prosodic modifications of IDS to real-world language-learning environments, highlighting some challenges of scaling up analyses of IDS to larger datasets that better capture children’s actual input.
  • Yu, J., Mailhammer, R., & Cutler, A. (2020). Vocabulary structure affects word recognition: Evidence from German listeners. In N. Minematsu, M. Kondo, T. Arai, & R. Hayashi (Eds.), Proceedings of Speech Prosody 2020 (pp. 474-478). Tokyo: ISCA. doi:10.21437/SpeechProsody.2020-97.

    Abstract

    Lexical stress is realised similarly in English, German, and Dutch. On a suprasegmental level, stressed syllables tend to be longer and more acoustically salient than unstressed syllables; segmentally, vowels in unstressed syllables are often reduced. The frequency of unreduced unstressed syllables (where only the suprasegmental cues indicate lack of stress) however, differs across the languages. The present studies test whether listener behaviour is affected by these vocabulary differences, by investigating German listeners’ use of suprasegmental cues to lexical stress in German and English word recognition. In a forced-choice identification task, German listeners correctly assigned single-syllable fragments (e.g., Kon-) to one of two words differing in stress (KONto, konZEPT). Thus, German listeners can exploit suprasegmental information for identifying words. German listeners also performed above chance in a similar task in English (with, e.g., DIver, diVERT), i.e., their sensitivity to these cues also transferred to a nonnative language. An English listener group, in contrast, failed in the English fragment task. These findings mirror vocabulary patterns: German has more words with unreduced unstressed syllables than English does.
  • Mengede, J., Devanna, P., Hörpel, S. G., Firzla, U., & Vernes, S. C. (2020). Studying the genetic bases of vocal learning in bats. In A. Ravignani, C. Barbieri, M. Flaherty, Y. Jadoul, E. Lattenkamp, H. Little, M. Martins, K. Mudd, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 13th International Conference (Evolang13) (pp. 280-282). Nijmegen: The Evolution of Language Conferences.
  • Mudd, K., Lutzenberger, H., De Vos, C., Fikkert, P., Crasborn, O., & De Boer, B. (2020). How does social structure shape language variation? A case study of the Kata Kolok lexicon. In A. Ravignani, C. Barbieri, M. Flaherty, Y. Jadoul, E. Lattenkamp, H. Little, M. Martins, K. Mudd, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 13th International Conference (Evolang13) (pp. 302-304). Nijmegen: The Evolution of Language Conferences.
  • Ozyurek, A. (2020). From hands to brains: How does human body talk, think and interact in face-to-face language use? In K. Truong, D. Heylen, & M. Czerwinski (Eds.), ICMI '20: Proceedings of the 2020 International Conference on Multimodal Interaction (pp. 1-2). New York, NY, USA: Association for Computing Machinery. doi:10.1145/3382507.3419442.
  • Rasenberg, M., Dingemanse, M., & Ozyurek, A. (2020). Lexical and gestural alignment in interaction and the emergence of novel shared symbols. In A. Ravignani, C. Barbieri, M. Flaherty, Y. Jadoul, E. Lattenkamp, H. Little, M. Martins, K. Mudd, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 13th International Conference (Evolang13) (pp. 356-358). Nijmegen: The Evolution of Language Conferences.
  • Raviv, L., Meyer, A. S., & Lev-Ari, S. (2020). Network structure and the cultural evolution of linguistic structure: A group communication experiment. In A. Ravignani, C. Barbieri, M. Flaherty, Y. Jadoul, E. Lattenkamp, H. Little, M. Martins, K. Mudd, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 13th International Conference (Evolang13) (pp. 359-361). Nijmegen: The Evolution of Language Conferences.
  • de Reus, K., Carlson, D., Jadoul, Y., Lowry, A., Gross, S., Garcia, M., Salazar Casals, A., Rubio-García, A., Haas, C. E., De Boer, B., & Ravignani, A. (2020). Relationships between vocal ontogeny and vocal tract anatomy in harbour seals (Phoca vitulina). In A. Ravignani, C. Barbieri, M. Flaherty, Y. Jadoul, E. Lattenkamp, H. Little, M. Martins, K. Mudd, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 13th International Conference (Evolang13) (pp. 63-66). Nijmegen: The Evolution of Language Conferences.
  • Seidlmayer, E., Voß, J., Melnychuk, T., Galke, L., Tochtermann, K., Schultz, C., & Förstner, K. U. (2020). ORCID for Wikidata. Data enrichment for scientometric applications. In L.-A. Kaffee, O. Tifrea-Marciuska, E. Simperl, & D. Vrandečić (Eds.), Proceedings of the 1st Wikidata Workshop (Wikidata 2020). Aachen, Germany: CEUR Workshop Proceedings.

    Abstract

    Due to its numerous bibliometric entries of scholarly articles and connected information Wikidata can serve as an open and rich source for deep scientometrical analyses. However, there are currently certain limitations: While 31.5% of all Wikidata entries represent scientific articles, only 8.9% are entries describing a person and the number of entries researcher is accordingly even lower. Another issue is the frequent absence of established relations between the scholarly article item and the author item although the author is already listed in Wikidata. To fill this gap and to improve the content of Wikidata in general, we established a workflow for matching authors and scholarly publications by integrating data from the ORCID (Open Researcher and Contributor ID) database. By this approach we were able to extend Wikidata by more than 12k author-publication relations and the method can be transferred to other enrichments based on ORCID data. This is extension is beneficial for Wikidata users performing bibliometrical analyses or using such metadata for other purposes.
  • Ter Bekke, M., Drijvers, L., & Holler, J. (2020). The predictive potential of hand gestures during conversation: An investigation of the timing of gestures in relation to speech. In Proceedings of the 7th GESPIN - Gesture and Speech in Interaction Conference. Stockholm: KTH Royal Institute of Technology.

    Abstract

    In face-to-face conversation, recipients might use the bodily movements of the speaker (e.g. gestures) to facilitate language processing. It has been suggested that one way through which this facilitation may happen is prediction. However, for this to be possible, gestures would need to precede speech, and it is unclear whether this is true during natural conversation. In a corpus of Dutch conversations, we annotated hand gestures that represent semantic information and occurred during questions, and the word(s) which corresponded most closely to the gesturally depicted meaning. Thus, we tested whether representational gestures temporally precede their lexical affiliates. Further, to see whether preceding gestures may indeed facilitate language processing, we asked whether the gesture-speech asynchrony predicts the response time to the question the gesture is part of. Gestures and their strokes (most meaningful movement component) indeed preceded the corresponding lexical information, thus demonstrating their predictive potential. However, while questions with gestures got faster responses than questions without, there was no evidence that questions with larger gesture-speech asynchronies get faster responses. These results suggest that gestures indeed have the potential to facilitate predictive language processing, but further analyses on larger datasets are needed to test for links between asynchrony and processing advantages.
  • Thompson, B., Raviv, L., & Kirby, S. (2020). Complexity can be maintained in small populations: A model of lexical variability in emerging sign languages. In A. Ravignani, C. Barbieri, M. Flaherty, Y. Jadoul, E. Lattenkamp, H. Little, M. Martins, K. Mudd, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 13th International Conference (Evolang13) (pp. 440-442). Nijmegen: The Evolution of Language Conferences.
  • Tsoukala, C., Frank, S. L., Van den Bosch, A., Kroff, J. V., & Broersma, M. (2020). Simulating Spanish-English code-switching: El modelo está generating code-switches. In E. Chersoni, C. Jacobs, Y. Oseki, L. Prévot, & E. Santus (Eds.), Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics (pp. 20-29). Stroudsburg, PA, USA: Association for Computational Linguistics (ACL).

    Abstract

    Multilingual speakers are able to switch from one language to the other (“code-switch”) be- tween or within sentences. Because the under- lying cognitive mechanisms are not well un- derstood, in this study we use computational cognitive modeling to shed light on the pro- cess of code-switching. We employed the Bilingual Dual-path model, a Recurrent Neu- ral Network of bilingual sentence production (Tsoukala et al., 2017) and simulated sentence production in simultaneous Spanish-English bilinguals. Our first goal was to investigate whether the model would code-switch with- out being exposed to code-switched training input. The model indeed produced code- switches even without any exposure to such input and the patterns of code-switches are in line with earlier linguistic work (Poplack, 1980). The second goal of this study was to investigate an auxiliary phrase asymmetry that exists in Spanish-English code-switched pro- duction. Using this cognitive model, we ex- amined a possible cause for this asymmetry. To our knowledge, this is the first computa- tional cognitive model that aims to simulate code-switched sentence production.
  • Van Arkel, J., Woensdregt, M., Dingemanse, M., & Blokpoel, M. (2020). A simple repair mechanism can alleviate computational demands of pragmatic reasoning: simulations and complexity analysis. In R. Fernández, & T. Linzen (Eds.), Proceedings of the 24th Conference on Computational Natural Language Learning (CoNLL 2020) (pp. 177-194). Stroudsburg, PA, USA: The Association for Computational Linguistics. doi:10.18653/v1/2020.conll-1.14.

    Abstract

    How can people communicate successfully while keeping resource costs low in the face of ambiguity? We present a principled theoretical analysis comparing two strategies for disambiguation in communication: (i) pragmatic reasoning, where communicators reason about each other, and (ii) other-initiated repair, where communicators signal and resolve trouble interactively. Using agent-based simulations and computational complexity analyses, we compare the efficiency of these strategies in terms of communicative success, computation cost and interaction cost. We show that agents with a simple repair mechanism can increase efficiency, compared to pragmatic agents, by reducing their computational burden at the cost of longer interactions. We also find that efficiency is highly contingent on the mechanism, highlighting the importance of explicit formalisation and computational rigour.
  • Van den Heuvel, H., Oostdijk, N., Rowland, C. F., & Trilsbeek, P. (2020). The CLARIN Knowledge Centre for Atypical Communication Expertise. In N. Calzolari, F. Béchet, P. Blache, K. Choukri, C. Cieri, T. Declerck, S. Goggi, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk, & S. Piperidis (Eds.), Proceedings of the 12th Language Resources and Evaluation Conference (LREC 2020) (pp. 3312-3316). Marseille, France: European Language Resources Association.

    Abstract

    This paper introduces a new CLARIN Knowledge Center which is the K-Centre for Atypical Communication Expertise (ACE for short) which has been established at the Centre for Language and Speech Technology (CLST) at Radboud University. Atypical communication is an umbrella term used here to denote language use by second language learners, people with language disorders or those suffering from language disabilities, but also more broadly by bilinguals and users of sign languages. It involves multiple modalities (text, speech, sign, gesture) and encompasses different developmental stages. ACE closely collaborates with The Language Archive (TLA) at the Max Planck Institute for Psycholinguistics in order to safeguard GDPR-compliant data storage and access. We explain the mission of ACE and show its potential on a number of showcases and a use case.
  • Vernes, S. C. (2020). Understanding bat vocal learning to gain insight into speech and language. In A. Ravignani, C. Barbieri, M. Flaherty, Y. Jadoul, E. Lattenkamp, H. Little, M. Martins, K. Mudd, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 13th International Conference (Evolang13) (pp. 6). Nijmegen: The Evolution of Language Conferences.
  • Woensdregt, M., & Dingemanse, M. (2020). Other-initiated repair can facilitate the emergence of compositional language. In A. Ravignani, C. Barbieri, M. Flaherty, Y. Jadoul, E. Lattenkamp, H. Little, M. Martins, K. Mudd, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 13th International Conference (Evolang13) (pp. 474-476). Nijmegen: The Evolution of Language Conferences.
  • Yang, J., Van den Bosch, A., & Frank, S. L. (2020). Less is Better: A cognitively inspired unsupervised model for language segmentation. In M. Zock, E. Chersoni, A. Lenci, & E. Santus (Eds.), Proceedings of the Workshop on the Cognitive Aspects of the Lexicon ( 28th International Conference on Computational Linguistics) (pp. 33-45). Stroudsburg: Association for Computational Linguistics.

    Abstract

    Language users process utterances by segmenting them into many cognitive units, which vary in their sizes and linguistic levels. Although we can do such unitization/segmentation easily, its cognitive mechanism is still not clear. This paper proposes an unsupervised model, Less-is-Better (LiB), to simulate the human cognitive process with respect to language unitization/segmentation. LiB follows the principle of least effort and aims to build a lexicon which minimizes the number of unit tokens (alleviating the effort of analysis) and number of unit types (alleviating the effort of storage) at the same time on any given corpus. LiB’s workflow is inspired by empirical cognitive phenomena. The design makes the mechanism of LiB cognitively plausible and the computational requirement light-weight. The lexicon generated by LiB performs the best among different types of lexicons (e.g. ground-truth words) both from an information-theoretical view and a cognitive view, which suggests that the LiB lexicon may be a plausible proxy of the mental lexicon.

    Additional information

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  • Alhama, R. G., Siegelman, N., Frost, R., & Armstrong, B. C. (2019). The role of information in visual word recognition: A perceptually-constrained connectionist account. In A. Goel, C. Seifert, & C. Freksa (Eds.), Proceedings of the 41st Annual Meeting of the Cognitive Science Society (CogSci 2019) (pp. 83-89). Austin, TX: Cognitive Science Society.

    Abstract

    Proficient readers typically fixate near the center of a word, with a slight bias towards word onset. We explore a novel account of this phenomenon based on combining information-theory with visual perceptual constraints in a connectionist model of visual word recognition. This account posits that the amount of information-content available for word identification varies across fixation locations and across languages, thereby explaining the overall fixation location bias in different languages, making the novel prediction that certain words are more readily identified when fixating at an atypical fixation location, and predicting specific cross-linguistic differences. We tested these predictions across several simulations in English and Hebrew, and in a pilot behavioral experiment. Results confirmed that the bias to fixate closer to word onset aligns with maximizing information in the visual signal, that some words are more readily identified at atypical fixation locations, and that these effects vary to some degree across languages.
  • Bentum, M., Ten Bosch, L., Van den Bosch, A., & Ernestus, M. (2019). Quantifying expectation modulation in human speech processing. In Proceedings of Interspeech 2019 (pp. 2270-2274). doi:10.21437/Interspeech.2019-2685.

    Abstract

    The mismatch between top-down predicted and bottom-up perceptual input is an important mechanism of perception according to the predictive coding framework (Friston, [1]). In this paper we develop and validate a new information-theoretic measure that quantifies the mismatch between expected and observed auditory input during speech processing. We argue that such a mismatch measure is useful for the study of speech processing. To compute the mismatch measure, we use naturalistic speech materials containing approximately 50,000 word tokens. For each word token we first estimate the prior word probability distribution with the aid of statistical language modelling, and next use automatic speech recognition to update this word probability distribution based on the unfolding speech signal. We validate the mismatch measure with multiple analyses, and show that the auditory-based update improves the probability of the correct word and lowers the uncertainty of the word probability distribution. Based on these results, we argue that it is possible to explicitly estimate the mismatch between predicted and perceived speech input with the cross entropy between word expectations computed before and after an auditory update.
  • Bentum, M., Ten Bosch, L., Van den Bosch, A., & Ernestus, M. (2019). Listening with great expectations: An investigation of word form anticipations in naturalistic speech. In Proceedings of Interspeech 2019 (pp. 2265-2269). doi:10.21437/Interspeech.2019-2741.

    Abstract

    The event-related potential (ERP) component named phonological mismatch negativity (PMN) arises when listeners hear an unexpected word form in a spoken sentence [1]. The PMN is thought to reflect the mismatch between expected and perceived auditory speech input. In this paper, we use the PMN to test a central premise in the predictive coding framework [2], namely that the mismatch between prior expectations and sensory input is an important mechanism of perception. We test this with natural speech materials containing approximately 50,000 word tokens. The corresponding EEG-signal was recorded while participants (n = 48) listened to these materials. Following [3], we quantify the mismatch with two word probability distributions (WPD): a WPD based on preceding context, and a WPD that is additionally updated based on the incoming audio of the current word. We use the between-WPD cross entropy for each word in the utterances and show that a higher cross entropy correlates with a more negative PMN. Our results show that listeners anticipate auditory input while processing each word in naturalistic speech. Moreover, complementing previous research, we show that predictive language processing occurs across the whole probability spectrum.
  • Brehm, L., Jackson, C. N., & Miller, K. L. (2019). Incremental interpretation in the first and second language. In M. Brown, & B. Dailey (Eds.), BUCLD 43: Proceedings of the 43rd annual Boston University Conference on Language Development (pp. 109-122). Sommerville, MA: Cascadilla Press.
  • Bruggeman, L., & Cutler, A. (2019). The dynamics of lexical activation and competition in bilinguals’ first versus second language. In S. Calhoun, P. Escudero, M. Tabain, & P. Warren (Eds.), Proceedings of the 19th International Congress of Phonetic Sciences (ICPhS 20195) (pp. 1342-1346). Canberra, Australia: Australasian Speech Science and Technology Association Inc.

    Abstract

    Speech input causes listeners to activate multiple candidate words which then compete with one another. These include onset competitors, that share a beginning (bumper, butter), but also, counterintuitively, rhyme competitors, sharing an ending (bumper, jumper). In L1, competition is typically stronger for onset than for rhyme. In L2, onset competition has been attested but rhyme competition has heretofore remained largely unexamined. We assessed L1 (Dutch) and L2 (English) word recognition by the same late-bilingual individuals. In each language, eye gaze was recorded as listeners heard sentences and viewed sets of drawings: three unrelated, one depicting an onset or rhyme competitor of a word in the input. Activation patterns revealed substantial onset competition but no significant rhyme competition in either L1 or L2. Rhyme competition may thus be a “luxury” feature of maximally efficient listening, to be abandoned when resources are scarcer, as in listening by late bilinguals, in either language.
  • Cutler, A., Burchfield, A., & Antoniou, M. (2019). A criterial interlocutor tally for successful talker adaptation? In S. Calhoun, P. Escudero, M. Tabain, & P. Warren (Eds.), Proceedings of the 19th International Congress of Phonetic Sciences (ICPhS 20195) (pp. 1485-1489). Canberra, Australia: Australasian Speech Science and Technology Association Inc.

    Abstract

    Part of the remarkable efficiency of listening is accommodation to unfamiliar talkers’ specific pronunciations by retuning of phonemic intercategory boundaries. Such retuning occurs in second (L2) as well as first language (L1); however, recent research with emigrés revealed successful adaptation in the environmental L2 but, unprecedentedly, not in L1 despite continuing L1 use. A possible explanation involving relative exposure to novel talkers is here tested in heritage language users with Mandarin as family L1 and English as environmental language. In English, exposure to an ambiguous sound in disambiguating word contexts prompted the expected adjustment of phonemic boundaries in subsequent categorisation. However, no adjustment occurred in Mandarin, again despite regular use. Participants reported highly asymmetric interlocutor counts in the two languages. We conclude that successful retuning ability requires regular exposure to novel talkers in the language in question, a criterion not met for the emigrés’ or for these heritage users’ L1.
  • Dideriksen, C., Fusaroli, R., Tylén, K., Dingemanse, M., & Christiansen, M. H. (2019). Contextualizing Conversational Strategies: Backchannel, Repair and Linguistic Alignment in Spontaneous and Task-Oriented Conversations. In A. K. Goel, C. M. Seifert, & C. Freksa (Eds.), Proceedings of the 41st Annual Conference of the Cognitive Science Society (CogSci 2019) (pp. 261-267). Montreal, QB: Cognitive Science Society.

    Abstract

    Do interlocutors adjust their conversational strategies to the specific contextual demands of a given situation? Prior studies have yielded conflicting results, making it unclear how strategies vary with demands. We combine insights from qualitative and quantitative approaches in a within-participant experimental design involving two different contexts: spontaneously occurring conversations (SOC) and task-oriented conversations (TOC). We systematically assess backchanneling, other-repair and linguistic alignment. We find that SOC exhibit a higher number of backchannels, a reduced and more generic repair format and higher rates of lexical and syntactic alignment. TOC are characterized by a high number of specific repairs and a lower rate of lexical and syntactic alignment. However, when alignment occurs, more linguistic forms are aligned. The findings show that conversational strategies adapt to specific contextual demands.
  • Felker, E. R., Ernestus, M., & Broersma, M. (2019). Evaluating dictation task measures for the study of speech perception. In S. Calhoun, P. Escudero, M. Tabain, & P. Warren (Eds.), Proceedings of the 19th International Congress of Phonetic Sciences (ICPhS 2019) (pp. 383-387). Canberra, Australia: Australasian Speech Science and Technology Association Inc.

    Abstract

    This paper shows that the dictation task, a well- known testing instrument in language education, has untapped potential as a research tool for studying speech perception. We describe how transcriptions can be scored on measures of lexical, orthographic, phonological, and semantic similarity to target phrases to provide comprehensive information about accuracy at different processing levels. The former three measures are automatically extractable, increasing objectivity, and the middle two are gradient, providing finer-grained information than traditionally used. We evaluate the measures in an English dictation task featuring phonetically reduced continuous speech. Whereas the lexical and orthographic measures emphasize listeners’ word identification difficulties, the phonological measure demonstrates that listeners can often still recover phonological features, and the semantic measure captures their ability to get the gist of the utterances. Correlational analyses and a discussion of practical and theoretical considerations show that combining multiple measures improves the dictation task’s utility as a research tool.
  • Felker, E. R., Ernestus, M., & Broersma, M. (2019). Lexically guided perceptual learning of a vowel shift in an interactive L2 listening context. In Proceedings of Interspeech 2019 (pp. 3123-3127). doi:10.21437/Interspeech.2019-1414.

    Abstract

    Lexically guided perceptual learning has traditionally been studied with ambiguous consonant sounds to which native listeners are exposed in a purely receptive listening context. To extend previous research, we investigate whether lexically guided learning applies to a vowel shift encountered by non-native listeners in an interactive dialogue. Dutch participants played a two-player game in English in either a control condition, which contained no evidence for a vowel shift, or a lexically constraining condition, in which onscreen lexical information required them to re-interpret their interlocutor’s /ɪ/ pronunciations as representing /ε/. A phonetic categorization pre-test and post-test were used to assess whether the game shifted listeners’ phonemic boundaries such that more of the /ε/-/ɪ/ continuum came to be perceived as /ε/. Both listener groups showed an overall post-test shift toward /ɪ/, suggesting that vowel perception may be sensitive to directional biases related to properties of the speaker’s vowel space. Importantly, listeners in the lexically constraining condition made relatively more post-test /ε/ responses than the control group, thereby exhibiting an effect of lexically guided adaptation. The results thus demonstrate that non-native listeners can adjust their phonemic boundaries on the basis of lexical information to accommodate a vowel shift learned in interactive conversation.
  • Fisher, S. E., & Tilot, A. K. (Eds.). (2019). Bridging senses: Novel insights from synaesthesia [Special Issue]. Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences, 374.
  • Frost, R. L. A., Isbilen, E. S., Christiansen, M. H., & Monaghan, P. (2019). Testing the limits of non-adjacent dependency learning: Statistical segmentation and generalisation across domains. In A. K. Goel, C. M. Seifert, & C. Freksa (Eds.), Proceedings of the 41st Annual Meeting of the Cognitive Science Society (CogSci 2019) (pp. 1787-1793). Montreal, QB: Cognitive Science Society.

    Abstract

    Achieving linguistic proficiency requires identifying words from speech, and discovering the constraints that govern the way those words are used. In a recent study of non-adjacent dependency learning, Frost and Monaghan (2016) demonstrated that learners may perform these tasks together, using similar statistical processes - contrary to prior suggestions. However, in their study, non-adjacent dependencies were marked by phonological cues (plosive-continuant-plosive structure), which may have influenced learning. Here, we test the necessity of these cues by comparing learning across three conditions; fixed phonology, which contains these cues, varied phonology, which omits them, and shapes, which uses visual shape sequences to assess the generality of statistical processing for these tasks. Participants segmented the sequences and generalized the structure in both auditory conditions, but learning was best when phonological cues were present. Learning was around chance on both tasks for the visual shapes group, indicating statistical processing may critically differ across domains.
  • Galke, L., Vagliano, I., & Scherp, A. (2019). Can graph neural networks go „online“? An analysis of pretraining and inference. In Proceedings of the Representation Learning on Graphs and Manifolds: ICLR2019 Workshop.

    Abstract

    Large-scale graph data in real-world applications is often not static but dynamic, i. e., new nodes and edges appear over time. Current graph convolution approaches are promising, especially, when all the graph’s nodes and edges are available dur- ing training. When unseen nodes and edges are inserted after training, it is not yet evaluated whether up-training or re-training from scratch is preferable. We construct an experimental setup, in which we insert previously unseen nodes and edges after training and conduct a limited amount of inference epochs. In this setup, we compare adapting pretrained graph neural networks against retraining from scratch. Our results show that pretrained models yield high accuracy scores on the unseen nodes and that pretraining is preferable over retraining from scratch. Our experiments represent a first step to evaluate and develop truly online variants of graph neural networks.
  • Galke, L., Melnychuk, T., Seidlmayer, E., Trog, S., Foerstner, K., Schultz, C., & Tochtermann, K. (2019). Inductive learning of concept representations from library-scale bibliographic corpora. In K. David, K. Geihs, M. Lange, & G. Stumme (Eds.), Informatik 2019: 50 Jahre Gesellschaft für Informatik - Informatik für Gesellschaft (pp. 219-232). Bonn: Gesellschaft für Informatik e.V. doi:10.18420/inf2019_26.
  • Goldrick, M., Brehm, L., Pyeong Whan, C., & Smolensky, P. (2019). Transient blend states and discrete agreement-driven errors in sentence production. In G. J. Snover, M. Nelson, B. O'Connor, & J. Pater (Eds.), Proceedings of the Society for Computation in Linguistics (SCiL 2019) (pp. 375-376). doi:10.7275/n0b2-5305.
  • Hahn, L. E., Ten Buuren, M., De Nijs, M., Snijders, T. M., & Fikkert, P. (2019). Acquiring novel words in a second language through mutual play with child songs - The Noplica Energy Center. In L. Nijs, H. Van Regenmortel, & C. Arculus (Eds.), MERYC19 Counterpoints of the senses: Bodily experiences in musical learning (pp. 78-87). Ghent, Belgium: EuNet MERYC 2019.

    Abstract

    Child songs are a great source for linguistic learning. Here we explore whether children can acquire novel words in a second language by playing a game featuring child songs in a playhouse. We present data from three studies that serve as scientific proof for the functionality of one game of the playhouse: the Energy Center. For this game, three hand-bikes were mounted on a panel. When children start moving the hand-bikes, child songs start playing simultaneously. Once the children produce enough energy with the hand-bikes, the songs are additionally accompanied with the sounds of musical instruments. In our studies, children executed a picture-selection task to evaluate whether they acquired new vocabulary from the songs presented during the game. Two of our studies were run in the field, one at a Dutch and one at an Indian pre-school. The third study features data from a more controlled laboratory setting. Our results partly confirm that the Energy Center is a successful means to support vocabulary acquisition in a second language. More research with larger sample sizes and longer access to the Energy Center is needed to evaluate the overall functionality of the game. Based on informal observations at our test sites, however, we are certain that children do pick up linguistic content from the songs during play, as many of the children repeat words and phrases from songs they heard. We will pick up upon these promising observations during future studies
  • Heilbron, M., Ehinger, B., Hagoort, P., & De Lange, F. P. (2019). Tracking naturalistic linguistic predictions with deep neural language models. In Proceedings of the 2019 Conference on Cognitive Computational Neuroscience (pp. 424-427). doi:10.32470/CCN.2019.1096-0.

    Abstract

    Prediction in language has traditionally been studied using simple designs in which neural responses to expected and unexpected words are compared in a categorical fashion. However, these designs have been contested as being ‘prediction encouraging’, potentially exaggerating the importance of prediction in language understanding. A few recent studies have begun to address these worries by using model-based approaches to probe the effects of linguistic predictability in naturalistic stimuli (e.g. continuous narrative). However, these studies so far only looked at very local forms of prediction, using models that take no more than the prior two words into account when computing a word’s predictability. Here, we extend this approach using a state-of-the-art neural language model that can take roughly 500 times longer linguistic contexts into account. Predictability estimates fromthe neural network offer amuch better fit to EEG data from subjects listening to naturalistic narrative than simpler models, and reveal strong surprise responses akin to the P200 and N400. These results show that predictability effects in language are not a side-effect of simple designs, and demonstrate the practical use of recent advances in AI for the cognitive neuroscience of language.
  • Joo, H., Jang, J., Kim, S., Cho, T., & Cutler, A. (2019). Prosodic structural effects on coarticulatory vowel nasalization in Australian English in comparison to American English. In S. Calhoun, P. Escudero, M. Tabain, & P. Warren (Eds.), Proceedings of the 19th International Congress of Phonetic Sciences (ICPhS 20195) (pp. 835-839). Canberra, Australia: Australasian Speech Science and Technology Association Inc.

    Abstract

    This study investigates effects of prosodic factors (prominence, boundary) on coarticulatory Vnasalization in Australian English (AusE) in CVN and NVC in comparison to those in American English (AmE). As in AmE, prominence was found to lengthen N, but to reduce V-nasalization, enhancing N’s nasality and V’s orality, respectively (paradigmatic contrast enhancement). But the prominence effect in CVN was more robust than that in AmE. Again similar to findings in AmE, boundary induced a reduction of N-duration and V-nasalization phrase-initially (syntagmatic contrast enhancement), and increased the nasality of both C and V phrasefinally. But AusE showed some differences in terms of the magnitude of V nasalization and N duration. The results suggest that the linguistic contrast enhancements underlie prosodic-structure modulation of coarticulatory V-nasalization in comparable ways across dialects, while the fine phonetic detail indicates that the phonetics-prosody interplay is internalized in the individual dialect’s phonetic grammar.
  • Mai, F., Galke, L., & Scherp, A. (2019). CBOW is not all you need: Combining CBOW with the compositional matrix space model. In Proceedings of the Seventh International Conference on Learning Representations (ICLR 2019). OpenReview.net.

    Abstract

    Continuous Bag of Words (CBOW) is a powerful text embedding method. Due to its strong capabilities to encode word content, CBOW embeddings perform well on a wide range of downstream tasks while being efficient to compute. However, CBOW is not capable of capturing the word order. The reason is that the computation of CBOW's word embeddings is commutative, i.e., embeddings of XYZ and ZYX are the same. In order to address this shortcoming, we propose a learning algorithm for the Continuous Matrix Space Model, which we call Continual Multiplication of Words (CMOW). Our algorithm is an adaptation of word2vec, so that it can be trained on large quantities of unlabeled text. We empirically show that CMOW better captures linguistic properties, but it is inferior to CBOW in memorizing word content. Motivated by these findings, we propose a hybrid model that combines the strengths of CBOW and CMOW. Our results show that the hybrid CBOW-CMOW-model retains CBOW's strong ability to memorize word content while at the same time substantially improving its ability to encode other linguistic information by 8%. As a result, the hybrid also performs better on 8 out of 11 supervised downstream tasks with an average improvement of 1.2%.
  • Mamus, E., Rissman, L., Majid, A., & Ozyurek, A. (2019). Effects of blindfolding on verbal and gestural expression of path in auditory motion events. In A. K. Goel, C. M. Seifert, & C. C. Freksa (Eds.), Proceedings of the 41st Annual Meeting of the Cognitive Science Society (CogSci 2019) (pp. 2275-2281). Montreal, QB: Cognitive Science Society.

    Abstract

    Studies have claimed that blind people’s spatial representations are different from sighted people, and blind people display superior auditory processing. Due to the nature of auditory and haptic information, it has been proposed that blind people have spatial representations that are more sequential than sighted people. Even the temporary loss of sight—such as through blindfolding—can affect spatial representations, but not much research has been done on this topic. We compared blindfolded and sighted people’s linguistic spatial expressions and non-linguistic localization accuracy to test how blindfolding affects the representation of path in auditory motion events. We found that blindfolded people were as good as sighted people when localizing simple sounds, but they outperformed sighted people when localizing auditory motion events. Blindfolded people’s path related speech also included more sequential, and less holistic elements. Our results indicate that even temporary loss of sight influences spatial representations of auditory motion events
  • Moisik, S. R., Zhi Yun, D. P., & Dediu, D. (2019). Active adjustment of the cervical spine during pitch production compensates for shape: The ArtiVarK study. In S. Calhoun, P. Escudero, M. Tabain, & P. Warren (Eds.), Proceedings of the 19th International Congress of Phonetic Sciences (ICPhS 20195) (pp. 864-868). Canberra, Australia: Australasian Speech Science and Technology Association Inc.

    Abstract

    The anterior lordosis of the cervical spine is thought to contribute to pitch (fo) production by influencing cricoid rotation as a function of larynx height. This study examines the matter of inter-individual variation in cervical spine shape and whether this has an influence on how fo is produced along increasing or decreasing scales, using the ArtiVarK dataset, which contains real-time MRI pitch production data. We find that the cervical spine actively participates in fo production, but the amount of displacement depends on individual shape. In general, anterior spine motion (tending toward cervical lordosis) occurs for low fo, while posterior movement (tending towards cervical kyphosis) occurs for high fo.
  • Nijveld, A., Ten Bosch, L., & Ernestus, M. (2019). ERP signal analysis with temporal resolution using a time window bank. In Proceedings of Interspeech 2019 (pp. 1208-1212). doi:10.21437/Interspeech.2019-2729.

    Abstract

    In order to study the cognitive processes underlying speech comprehension, neuro-physiological measures (e.g., EEG and MEG), or behavioural measures (e.g., reaction times and response accuracy) can be applied. Compared to behavioural measures, EEG signals can provide a more fine-grained and complementary view of the processes that take place during the unfolding of an auditory stimulus. EEG signals are often analysed after having chosen specific time windows, which are usually based on the temporal structure of ERP components expected to be sensitive to the experimental manipulation. However, as the timing of ERP components may vary between experiments, trials, and participants, such a-priori defined analysis time windows may significantly hamper the exploratory power of the analysis of components of interest. In this paper, we explore a wide-window analysis method applied to EEG signals collected in an auditory repetition priming experiment. This approach is based on a bank of temporal filters arranged along the time axis in combination with linear mixed effects modelling. Crucially, it permits a temporal decomposition of effects in a single comprehensive statistical model which captures the entire EEG trace.
  • Parhammer*, S. I., Ebersberg*, M., Tippmann*, J., Stärk*, K., Opitz, A., Hinger, B., & Rossi, S. (2019). The influence of distraction on speech processing: How selective is selective attention? In Proceedings of Interspeech 2019 (pp. 3093-3097). doi:10.21437/Interspeech.2019-2699.

    Abstract

    -* indicates shared first authorship - The present study investigated the effects of selective attention on the processing of morphosyntactic errors in unattended parts of speech. Two groups of German native (L1) speakers participated in the present study. Participants listened to sentences in which irregular verbs were manipulated in three different conditions (correct, incorrect but attested ablaut pattern, incorrect and crosslinguistically unattested ablaut pattern). In order to track fast dynamic neural reactions to the stimuli, electroencephalography was used. After each sentence, participants in Experiment 1 performed a semantic judgement task, which deliberately distracted the participants from the syntactic manipulations and directed their attention to the semantic content of the sentence. In Experiment 2, participants carried out a syntactic judgement task, which put their attention on the critical stimuli. The use of two different attentional tasks allowed for investigating the impact of selective attention on speech processing and whether morphosyntactic processing steps are performed automatically. In Experiment 2, the incorrect attested condition elicited a larger N400 component compared to the correct condition, whereas in Experiment 1 no differences between conditions were found. These results suggest that the processing of morphosyntactic violations in irregular verbs is not entirely automatic but seems to be strongly affected by selective attention.
  • Pouw, W., Paxton, A., Harrison, S. J., & Dixon, J. A. (2019). Acoustic specification of upper limb movement in voicing. In A. Grimminger (Ed.), Proceedings of the 6th Gesture and Speech in Interaction – GESPIN 6 (pp. 68-74). Paderborn: Universitaetsbibliothek Paderborn. doi:10.17619/UNIPB/1-812.
  • Pouw, W., & Dixon, J. A. (2019). Quantifying gesture-speech synchrony. In A. Grimminger (Ed.), Proceedings of the 6th Gesture and Speech in Interaction – GESPIN 6 (pp. 75-80). Paderborn: Universitaetsbibliothek Paderborn. doi:10.17619/UNIPB/1-812.

    Abstract

    Spontaneously occurring speech is often seamlessly accompanied by hand gestures. Detailed observations of video data suggest that speech and gesture are tightly synchronized in time, consistent with a dynamic interplay between body and mind. However, spontaneous gesturespeech synchrony has rarely been objectively quantified beyond analyses of video data, which do not allow for identification of kinematic properties of gestures. Consequently, the point in gesture which is held to couple with speech, the so-called moment of “maximum effort”, has been variably equated with the peak velocity, peak acceleration, peak deceleration, or the onset of the gesture. In the current exploratory report, we provide novel evidence from motiontracking and acoustic data that peak velocity is closely aligned, and shortly leads, the peak pitch (F0) of speech

    Additional information

    https://osf.io/9843h/
  • Rissman, L., & Majid, A. (2019). Agency drives category structure in instrumental events. In A. K. Goel, C. M. Seifert, & C. Freksa (Eds.), Proceedings of the 41st Annual Meeting of the Cognitive Science Society (CogSci 2019) (pp. 2661-2667). Montreal, QB: Cognitive Science Society.

    Abstract

    Thematic roles such as Agent and Instrument have a long-standing place in theories of event representation. Nonetheless, the structure of these categories has been difficult to determine. We investigated how instrumental events, such as someone slicing bread with a knife, are categorized in English. Speakers described a variety of typical and atypical instrumental events, and we determined the similarity structure of their descriptions using correspondence analysis. We found that events where the instrument is an extension of an intentional agent were most likely to elicit similar language, highlighting the importance of agency in structuring instrumental categories.
  • Schoenmakers, G.-J., & De Swart, P. (2019). Adverbial hurdles in Dutch scrambling. In A. Gattnar, R. Hörnig, M. Störzer, & S. Featherston (Eds.), Proceedings of Linguistic Evidence 2018: Experimental Data Drives Linguistic Theory (pp. 124-145). Tübingen: University of Tübingen.

    Abstract

    This paper addresses the role of the adverb in Dutch direct object scrambling constructions. We report four experiments in which we investigate whether the structural position and the scope sensitivity of the adverb affect acceptability judgments of scrambling constructions and native speakers' tendency to scramble definite objects. We conclude that the type of adverb plays a key role in Dutch word ordering preferences.
  • Schuerman, W. L., McQueen, J. M., & Meyer, A. S. (2019). Speaker statistical averageness modulates word recognition in adverse listening conditions. In S. Calhoun, P. Escudero, M. Tabain, & P. Warren (Eds.), Proceedings of the 19th International Congress of Phonetic Sciences (ICPhS 20195) (pp. 1203-1207). Canberra, Australia: Australasian Speech Science and Technology Association Inc.

    Abstract

    We tested whether statistical averageness (SA) at the level of the individual speaker could predict a speaker’s intelligibility. 28 female and 21 male speakers of Dutch were recorded producing 336 sentences, each containing two target nouns. Recordings were compared to those of all other same-sex speakers using dynamic time warping (DTW). For each sentence, the DTW distance constituted a metric of phonetic distance from one speaker to all other speakers. SA comprised the average of these distances. Later, the same participants performed a word recognition task on the target nouns in the same sentences, under three degraded listening conditions. In all three conditions, accuracy increased with SA. This held even when participants listened to their own utterances. These findings suggest that listeners process speech with respect to the statistical properties of the language spoken in their community, rather than using their own speech as a reference
  • Seidlmayer, E., Galke, L., Melnychuk, T., Schultz, C., Tochtermann, K., & Förstner, K. U. (2019). Take it personally - A Python library for data enrichment for infometrical applications. In M. Alam, R. Usbeck, T. Pellegrini, H. Sack, & Y. Sure-Vetter (Eds.), Proceedings of the Posters and Demo Track of the 15th International Conference on Semantic Systems co-located with 15th International Conference on Semantic Systems (SEMANTiCS 2019).

    Abstract

    Like every other social sphere, science is influenced by individual characteristics of researchers. However, for investigations on scientific networks, only little data about the social background of researchers, e.g. social origin, gender, affiliation etc., is available. This paper introduces ”Take it personally - TIP”, a conceptual model and library currently under development, which aims to support the semantic enrichment of publication databases with semantically related background information which resides elsewhere in the (semantic) web, such as Wikidata. The supplementary information enriches the original information in the publication databases and thus facilitates the creation of complex scientific knowledge graphs. Such enrichment helps to improve the scientometric analysis of scientific publications as they can also take social backgrounds of researchers into account and to understand social structure in research communities.
  • Seijdel, N., Sakmakidis, N., De Haan, E. H. F., Bohte, S. M., & Scholte, H. S. (2019). Implicit scene segmentation in deeper convolutional neural networks. In Proceedings of the 2019 Conference on Cognitive Computational Neuroscience (pp. 1059-1062). doi:10.32470/CCN.2019.1149-0.

    Abstract

    Feedforward deep convolutional neural networks (DCNNs) are matching and even surpassing human performance on object recognition. This performance suggests that activation of a loose collection of image features could support the recognition of natural object categories, without dedicated systems to solve specific visual subtasks. Recent findings in humans however, suggest that while feedforward activity may suffice for sparse scenes with isolated objects, additional visual operations ('routines') that aid the recognition process (e.g. segmentation or grouping) are needed for more complex scenes. Linking human visual processing to performance of DCNNs with increasing depth, we here explored if, how, and when object information is differentiated from the backgrounds they appear on. To this end, we controlled the information in both objects and backgrounds, as well as the relationship between them by adding noise, manipulating background congruence and systematically occluding parts of the image. Results indicated less distinction between object- and background features for more shallow networks. For those networks, we observed a benefit of training on segmented objects (as compared to unsegmented objects). Overall, deeper networks trained on natural (unsegmented) scenes seem to perform implicit 'segmentation' of the objects from their background, possibly by improved selection of relevant features.
  • Shen, C., & Janse, E. (2019). Articulatory control in speech production. In S. Calhoun, P. Escudero, M. Tabain, & P. Warren (Eds.), Proceedings of the 19th International Congress of Phonetic Sciences (ICPhS 2019) (pp. 2533-2537). Canberra, Australia: Australasian Speech Science and Technology Association Inc.
  • Shen, C., Cooke, M., & Janse, E. (2019). Individual articulatory control in speech enrichment. In M. Ochmann, M. Vorländer, & J. Fels (Eds.), Proceedings of the 23rd International Congress on Acoustics (pp. 5726-5730). Berlin: Deutsche Gesellschaft für Akustik.

    Abstract

    ndividual talkers may use various strategies to enrich their speech while speaking in noise (i.e., Lombard speech) to improve their intelligibility. The resulting acoustic-phonetic changes in Lombard speech vary amongst different speakers, but it is unclear what causes these talker differences, and what impact these differences have on intelligibility. This study investigates the potential role of articulatory control in talkers’ Lombard speech enrichment success. Seventy-eight speakers read out sentences in both their habitual style and in a condition where they were instructed to speak clearly while hearing loud speech-shaped noise. A diadochokinetic (DDK) speech task that requires speakers to repetitively produce word or non-word sequences as accurately and as rapidly as possible, was used to quantify their articulatory control. Individuals’ predicted intelligibility in both speaking styles (presented at -5 dB SNR) was measured using an acoustic glimpse-based metric: the High-Energy Glimpse Proportion (HEGP). Speakers’ HEGP scores show a clear effect of speaking condition (better HEGP scores in the Lombard than habitual condition), but no simple effect of articulatory control on HEGP, nor an interaction between speaking condition and articulatory control. This indicates that individuals’ speech enrichment success as measured by the HEGP metric was not predicted by DDK performance.
  • Ten Bosch, L., Mulder, K., & Boves, L. (2019). Phase synchronization between EEG signals as a function of differences between stimuli characteristics. In Proceedings of Interspeech 2019 (pp. 1213-1217). doi:10.21437/Interspeech.2019-2443.

    Abstract

    The neural processing of speech leads to specific patterns in the brain which can be measured as, e.g., EEG signals. When properly aligned with the speech input and averaged over many tokens, the Event Related Potential (ERP) signal is able to differentiate specific contrasts between speech signals. Well-known effects relate to the difference between expected and unexpected words, in particular in the N400, while effects in N100 and P200 are related to attention and acoustic onset effects. Most EEG studies deal with the amplitude of EEG signals over time, sidestepping the effect of phase and phase synchronization. This paper investigates the relation between phase in the EEG signals measured in an auditory lexical decision task by Dutch participants listening to full and reduced English word forms. We show that phase synchronization takes place across stimulus conditions, and that the so-called circular variance is narrowly related to the type of contrast between stimuli.
  • Ter Bekke, M., Ozyurek, A., & Ünal, E. (2019). Speaking but not gesturing predicts motion event memory within and across languages. In A. Goel, C. Seifert, & C. Freksa (Eds.), Proceedings of the 41st Annual Meeting of the Cognitive Science Society (CogSci 2019) (pp. 2940-2946). Montreal, QB: Cognitive Science Society.

    Abstract

    In everyday life, people see, describe and remember motion events. We tested whether the type of motion event information (path or manner) encoded in speech and gesture predicts which information is remembered and if this varies across speakers of typologically different languages. We focus on intransitive motion events (e.g., a woman running to a tree) that are described differently in speech and co-speech gesture across languages, based on how these languages typologically encode manner and path information (Kita & Özyürek, 2003; Talmy, 1985). Speakers of Dutch (n = 19) and Turkish (n = 22) watched and described motion events. With a surprise (i.e. unexpected) recognition memory task, memory for manner and path components of these events was measured. Neither Dutch nor Turkish speakers’ memory for manner went above chance levels. However, we found a positive relation between path speech and path change detection: participants who described the path during encoding were more accurate at detecting changes to the path of an event during the memory task. In addition, the relation between path speech and path memory changed with native language: for Dutch speakers encoding path in speech was related to improved path memory, but for Turkish speakers no such relation existed. For both languages, co-speech gesture did not predict memory speakers. We discuss the implications of these findings for our understanding of the relations between speech, gesture, type of encoding in language and memory.
  • Wagner, M. A., Broersma, M., McQueen, J. M., & Lemhöfer, K. (2019). Imitating speech in an unfamiliar language and an unfamiliar non-native accent in the native language. In S. Calhoun, P. Escudero, M. Tabain, & P. Warren (Eds.), Proceedings of the 19th International Congress of Phonetic Sciences (ICPhS 20195) (pp. 1362-1366). Canberra, Australia: Australasian Speech Science and Technology Association Inc.

    Abstract

    This study concerns individual differences in speech imitation ability and the role that lexical representations play in imitation. We examined 1) whether imitation of sounds in an unfamiliar language (L0) is related to imitation of sounds in an unfamiliar non-native accent in the speaker’s native language (L1) and 2) whether it is easier or harder to imitate speech when you know the words to be imitated. Fifty-nine native Dutch speakers imitated words with target vowels in Basque (/a/ and /e/) and Greekaccented Dutch (/i/ and /u/). Spectral and durational analyses of the target vowels revealed no relationship between the success of L0 and L1 imitation and no difference in performance between tasks (i.e., L1 imitation was neither aided nor blocked by lexical knowledge about the correct pronunciation). The results suggest instead that the relationship of the vowels to native phonological categories plays a bigger role in imitation
  • Wolf, M. C., Smith, A. C., Meyer, A. S., & Rowland, C. F. (2019). Modality effects in vocabulary acquisition. In A. K. Goel, C. M. Seifert, & C. Freksa (Eds.), Proceedings of the 41st Annual Meeting of the Cognitive Science Society (CogSci 2019) (pp. 1212-1218). Montreal, QB: Cognitive Science Society.

    Abstract

    It is unknown whether modality affects the efficiency with which humans learn novel word forms and their meanings, with previous studies reporting both written and auditory advantages. The current study implements controls whose absence in previous work likely offers explanation for such contradictory findings. In two novel word learning experiments, participants were trained and tested on pseudoword - novel object pairs, with controls on: modality of test, modality of meaning, duration of exposure and transparency of word form. In both experiments word forms were presented in either their written or spoken form, each paired with a pictorial meaning (novel object). Following a 20-minute filler task, participants were tested on their ability to identify the picture-word form pairs on which they were trained. A between subjects design generated four participant groups per experiment 1) written training, written test; 2) written training, spoken test; 3) spoken training, written test; 4) spoken training, spoken test. In Experiment 1 the written stimulus was presented for a time period equal to the duration of the spoken form. Results showed that when the duration of exposure was equal, participants displayed a written training benefit. Given words can be read faster than the time taken for the spoken form to unfold, in Experiment 2 the written form was presented for 300 ms, sufficient time to read the word yet 65% shorter than the duration of the spoken form. No modality effect was observed under these conditions, when exposure to the word form was equivalent. These results demonstrate, at least for proficient readers, that when exposure to the word form is controlled across modalities the efficiency with which word form-meaning associations are learnt does not differ. Our results therefore suggest that, although we typically begin as aural-only word learners, we ultimately converge on developing learning mechanisms that learn equally efficiently from both written and spoken materials.
  • Bentz, C., Dediu, D., Verkerk, A., & Jäger, G. (2018). Language family trees reflect geography and demography beyond neutral drift. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 38-40). Toruń, Poland: NCU Press. doi:10.12775/3991-1.006.
  • Brand, J., Monaghan, P., & Walker, P. (2018). Changing Signs: Testing How Sound-Symbolism Supports Early Word Learning. In C. Kalish, M. Rau, J. Zhu, & T. T. Rogers (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (CogSci 2018) (pp. 1398-1403). Austin, TX: Cognitive Science Society.

    Abstract

    Learning a language involves learning how to map specific forms onto their associated meanings. Such mappings can utilise arbitrariness and non-arbitrariness, yet, our understanding of how these two systems operate at different stages of vocabulary development is still not fully understood. The Sound-Symbolism Bootstrapping Hypothesis (SSBH) proposes that sound-symbolism is essential for word learning to commence, but empirical evidence of exactly how sound-symbolism influences language learning is still sparse. It may be the case that sound-symbolism supports acquisition of categories of meaning, or that it enables acquisition of individualized word meanings. In two Experiments where participants learned form-meaning mappings from either sound-symbolic or arbitrary languages, we demonstrate the changing roles of sound-symbolism and arbitrariness for different vocabulary sizes, showing that sound-symbolism provides an advantage for learning of broad categories, which may then transfer to support learning individual words, whereas an arbitrary language impedes acquisition of categories of sound to meaning.
  • Byun, K.-S., De Vos, C., Roberts, S. G., & Levinson, S. C. (2018). Interactive sequences modulate the selection of expressive forms in cross-signing. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 67-69). Toruń, Poland: NCU Press. doi:10.12775/3991-1.012.
  • Cristia, A., Ganesh, S., Casillas, M., & Ganapathy, S. (2018). Talker diarization in the wild: The case of child-centered daylong audio-recordings. In Proceedings of Interspeech 2018 (pp. 2583-2587). doi:10.21437/Interspeech.2018-2078.

    Abstract

    Speaker diarization (answering 'who spoke when') is a widely researched subject within speech technology. Numerous experiments have been run on datasets built from broadcast news, meeting data, and call centers—the task sometimes appears close to being solved. Much less work has begun to tackle the hardest diarization task of all: spontaneous conversations in real-world settings. Such diarization would be particularly useful for studies of language acquisition, where researchers investigate the speech children produce and hear in their daily lives. In this paper, we study audio gathered with a recorder worn by small children as they went about their normal days. As a result, each child was exposed to different acoustic environments with a multitude of background noises and a varying number of adults and peers. The inconsistency of speech and noise within and across samples poses a challenging task for speaker diarization systems, which we tackled via retraining and data augmentation techniques. We further studied sources of structured variation across raw audio files, including the impact of speaker type distribution, proportion of speech from children, and child age on diarization performance. We discuss the extent to which these findings might generalize to other samples of speech in the wild.
  • Ip, M. H. K., & Cutler, A. (2018). Asymmetric efficiency of juncture perception in L1 and L2. In K. Klessa, J. Bachan, A. Wagner, M. Karpiński, & D. Śledziński (Eds.), Proceedings of Speech Prosody 2018 (pp. 289-296). Baixas, France: ISCA. doi:10.21437/SpeechProsody.2018-59.

    Abstract

    In two experiments, Mandarin listeners resolved potential syntactic ambiguities in spoken utterances in (a) their native language (L1) and (b) English which they had learned as a second language (L2). A new disambiguation task was used, requiring speeded responses to select the correct meaning for structurally ambiguous sentences. Importantly, the ambiguities used in the study are identical in Mandarin and in English, and production data show that prosodic disambiguation of this type of ambiguity is also realised very similarly in the two languages. The perceptual results here showed however that listeners’ response patterns differed for L1 and L2, although there was a significant increase in similarity between the two response patterns with increasing exposure to the L2. Thus identical ambiguity and comparable disambiguation patterns in L1 and L2 do not lead to immediate application of the appropriate L1 listening strategy to L2; instead, it appears that such a strategy may have to be learned anew for the L2.
  • Ip, M. H. K., & Cutler, A. (2018). Cue equivalence in prosodic entrainment for focus detection. In J. Epps, J. Wolfe, J. Smith, & C. Jones (Eds.), Proceedings of the 17th Australasian International Conference on Speech Science and Technology (pp. 153-156).

    Abstract

    Using a phoneme detection task, the present series of experiments examines whether listeners can entrain to different combinations of prosodic cues to predict where focus will fall in an utterance. The stimuli were recorded by four female native speakers of Australian English who happened to have used different prosodic cues to produce sentences with prosodic focus: a combination of duration cues, mean and maximum F0, F0 range, and longer pre-target interval before the focused word onset, only mean F0 cues, only pre-target interval, and only duration cues. Results revealed that listeners can entrain in almost every condition except for where duration was the only reliable cue. Our findings suggest that listeners are flexible in the cues they use for focus processing.
  • Cutler, A., Burchfield, L. A., & Antoniou, M. (2018). Factors affecting talker adaptation in a second language. In J. Epps, J. Wolfe, J. Smith, & C. Jones (Eds.), Proceedings of the 17th Australasian International Conference on Speech Science and Technology (pp. 33-36).

    Abstract

    Listeners adapt rapidly to previously unheard talkers by adjusting phoneme categories using lexical knowledge, in a process termed lexically-guided perceptual learning. Although this is firmly established for listening in the native language (L1), perceptual flexibility in second languages (L2) is as yet less well understood. We report two experiments examining L1 and L2 perceptual learning, the first in Mandarin-English late bilinguals, the second in Australian learners of Mandarin. Both studies showed stronger learning in L1; in L2, however, learning appeared for the English-L1 group but not for the Mandarin-L1 group. Phonological mapping differences from the L1 to the L2 are suggested as the reason for this result.
  • Delgado, T., Ravignani, A., Verhoef, T., Thompson, B., Grossi, T., & Kirby, S. (2018). Cultural transmission of melodic and rhythmic universals: Four experiments and a model. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 89-91). Toruń, Poland: NCU Press. doi:10.12775/3991-1.019.
  • Duarte, R., Uhlmann, M., Van den Broek, D., Fitz, H., Petersson, K. M., & Morrison, A. (2018). Encoding symbolic sequences with spiking neural reservoirs. In Proceedings of the 2018 International Joint Conference on Neural Networks (IJCNN). doi:10.1109/IJCNN.2018.8489114.

    Abstract

    Biologically inspired spiking networks are an important tool to study the nature of computation and cognition in neural systems. In this work, we investigate the representational capacity of spiking networks engaged in an identity mapping task. We compare two schemes for encoding symbolic input, one in which input is injected as a direct current and one where input is delivered as a spatio-temporal spike pattern. We test the ability of networks to discriminate their input as a function of the number of distinct input symbols. We also compare performance using either membrane potentials or filtered spike trains as state variable. Furthermore, we investigate how the circuit behavior depends on the balance between excitation and inhibition, and the degree of synchrony and regularity in its internal dynamics. Finally, we compare different linear methods of decoding population activity onto desired target labels. Overall, our results suggest that even this simple mapping task is strongly influenced by design choices on input encoding, state-variables, circuit characteristics and decoding methods, and these factors can interact in complex ways. This work highlights the importance of constraining computational network models of behavior by available neurobiological evidence.
  • Ergin, R., Senghas, A., Jackendoff, R., & Gleitman, L. (2018). Structural cues for symmetry, asymmetry, and non-symmetry in Central Taurus Sign Language. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 104-106). Toruń, Poland: NCU Press. doi:10.12775/3991-1.025.
  • Galke, L., Gerstenkorn, G., & Scherp, A. (2018). A case study of closed-domain response suggestion with limited training data. In M. Elloumi, M. Granitzer, A. Hameurlain, C. Seifert, B. Stein, A. Min Tjoa, & R. Wagner (Eds.), Database and Expert Systems Applications: DEXA 2018 International Workshops, BDMICS, BIOKDD, and TIR, Regensburg, Germany, September 3–6, 2018, Proceedings (pp. 218-229). Cham, Switzerland: Springer.

    Abstract

    We analyze the problem of response suggestion in a closed domain along a real-world scenario of a digital library. We present a text-processing pipeline to generate question-answer pairs from chat transcripts. On this limited amount of training data, we compare retrieval-based, conditioned-generation, and dedicated representation learning approaches for response suggestion. Our results show that retrieval-based methods that strive to find similar, known contexts are preferable over parametric approaches from the conditioned-generation family, when the training data is limited. We, however, identify a specific representation learning approach that is competitive to the retrieval-based approaches despite the training data limitation.
  • Galke, L., Mai, F., & Vagliano, I. (2018). Multi-modal adversarial autoencoders for recommendations of citations and subject labels. In T. Mitrovic, J. Zhang, L. Chen, & D. Chin (Eds.), UMAP '18: Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization (pp. 197-205). New York: ACM. doi:10.1145/3209219.3209236.

    Abstract

    We present multi-modal adversarial autoencoders for recommendation and evaluate them on two different tasks: citation recommendation and subject label recommendation. We analyze the effects of adversarial regularization, sparsity, and different input modalities. By conducting 408 experiments, we show that adversarial regularization consistently improves the performance of autoencoders for recommendation. We demonstrate, however, that the two tasks differ in the semantics of item co-occurrence in the sense that item co-occurrence resembles relatedness in case of citations, yet implies diversity in case of subject labels. Our results reveal that supplying the partial item set as input is only helpful, when item co-occurrence resembles relatedness. When facing a new recommendation task it is therefore crucial to consider the semantics of item co-occurrence for the choice of an appropriate model.
  • Hopman, E., Thompson, B., Austerweil, J., & Lupyan, G. (2018). Predictors of L2 word learning accuracy: A big data investigation. In C. Kalish, M. Rau, J. Zhu, & T. T. Rogers (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (CogSci 2018) (pp. 513-518). Austin, TX: Cognitive Science Society.

    Abstract

    What makes some words harder to learn than others in a second language? Although some robust factors have been identified based on small scale experimental studies, many relevant factors are difficult to study in such experiments due to the amount of data necessary to test them. Here, we investigate what factors affect the ease of learning of a word in a second language using a large data set of users learning English as a second language through the Duolingo mobile app. In a regression analysis, we test and confirm the well-studied effect of cognate status on word learning accuracy. Furthermore, we find significant effects for both cross-linguistic semantic alignment and English semantic density, two novel predictors derived from large scale distributional models of lexical semantics. Finally, we provide data on several other psycholinguistically plausible word level predictors. We conclude with a discussion of the limits, benefits and future research potential of using big data for investigating second language learning.
  • Huettig, F., Kolinsky, R., & Lachmann, T. (Eds.). (2018). The effects of literacy on cognition and brain functioning [Special Issue]. Language, Cognition and Neuroscience, 33(3).
  • Isbilen, E., Frost, R. L. A., Monaghan, P., & Christiansen, M. (2018). Bridging artificial and natural language learning: Comparing processing- and reflection-based measures of learning. In C. Kalish, M. Rau, J. Zhu, & T. T. Rogers (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (CogSci 2018) (pp. 1856-1861). Austin, TX: Cognitive Science Society.

    Abstract

    A common assumption in the cognitive sciences is that artificial and natural language learning rely on shared mechanisms. However, attempts to bridge the two have yielded ambiguous results. We suggest that an empirical disconnect between the computations employed during learning and the methods employed at test may explain these mixed results. Further, we propose statistically-based chunking as a potential computational link between artificial and natural language learning. We compare the acquisition of non-adjacent dependencies to that of natural language structure using two types of tasks: reflection-based 2AFC measures, and processing-based recall measures, the latter being more computationally analogous to the processes used during language acquisition. Our results demonstrate that task-type significantly influences the correlations observed between artificial and natural language acquisition, with reflection-based and processing-based measures correlating within – but not across – task-type. These findings have fundamental implications for artificial-to-natural language comparisons, both methodologically and theoretically.

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