Publications

Displaying 1 - 100 of 130
  • Allen, S. E. M. (1998). A discourse-pragmatic explanation for the subject-object asymmetry in early null arguments. In A. Sorace, C. Heycock, & R. Shillcock (Eds.), Proceedings of the GALA '97 Conference on Language Acquisition (pp. 10-15). Edinburgh, UK: Edinburgh University Press.

    Abstract

    The present paper assesses discourse-pragmatic factors as a potential explanation for the subject-object assymetry in early child language. It identifies a set of factors which characterize typical situations of informativeness (Greenfield & Smith, 1976), and uses these factors to identify informative arguments in data from four children aged 2;0 through 3;6 learning Inuktitut as a first language. In addition, it assesses the extent of the links between features of informativeness on one hand and lexical vs. null and subject vs. object arguments on the other. Results suggest that a pragmatics account of the subject-object asymmetry can be upheld to a greater extent than previous research indicates, and that several of the factors characterizing informativeness are good indicators of those arguments which tend to be omitted in early child language.
  • Amatuni, A., Schroer, S. E., Zhang, Y., Peters, R. E., Reza, M. A., Crandall, D., & Yu, C. (2021). In-the-moment visual information from the infant's egocentric view determines the success of infant word learning: A computational study. 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. 265-271). Vienna: Cognitive Science Society.

    Abstract

    Infants learn the meaning of words from accumulated experiences of real-time interactions with their caregivers. To study the effects of visual sensory input on word learning, we recorded infant's view of the world using head-mounted eye trackers during free-flowing play with a caregiver. While playing, infants were exposed to novel label-object mappings and later learning outcomes for these items were tested after the play session. In this study we use a classification based approach to link properties of infants' visual scenes during naturalistic labeling moments to their word learning outcomes. We find that a model which integrates both highly informative and ambiguous sensory evidence is a better fit to infants' individual learning outcomes than models where either type of evidence is taken alone, and that raw labeling frequency is unable to account for the word learning differences we observe. Here we demonstrate how a computational model, using only raw pixels taken from the egocentric scene image, can derive insights on human language learning.
  • Anastasopoulos, A., Lekakou, M., Quer, J., Zimianiti, E., DeBenedetto, J., & Chiang, D. (2018). Part-of-speech tagging on an endangered language: a parallel Griko-Italian Resource. In Proceedings of the 27th International Conference on Computational Linguistics (COLING 2018) (pp. 2529-2539).

    Abstract

    Most work on part-of-speech (POS) tagging is focused on high resource languages, or examines low-resource and active learning settings through simulated studies. We evaluate POS tagging techniques on an actual endangered language, Griko. We present a resource that contains 114 narratives in Griko, along with sentence-level translations in Italian, and provides gold annotations for the test set. Based on a previously collected small corpus, we investigate several traditional methods, as well as methods that take advantage of monolingual data or project cross-lingual POS tags. We show that the combination of a semi-supervised method with cross-lingual transfer is more appropriate for this extremely challenging setting, with the best tagger achieving an accuracy of 72.9%. With an applied active learning scheme, which we use to collect sentence-level annotations over the test set, we achieve improvements of more than 21 percentage points
  • Bavin, E. L., & Kidd, E. (2000). Learning new verbs: Beyond the input. In C. Davis, T. J. Van Gelder, & R. Wales (Eds.), Cognitive Science in Australia, 2000: Proceedings of the Fifth Biennial Conference of the Australasian Cognitive Science Society.
  • 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.
  • Bodur, K., Branje, S., Peirolo, M., Tiscareno, I., & German, J. S. (2021). Domain-initial strengthening in Turkish: Acoustic cues to prosodic hierarchy in stop consonants. In Proceedings of Interspeech 2021 (pp. 1459-1463). doi:10.21437/Interspeech.2021-2230.

    Abstract

    Studies have shown that cross-linguistically, consonants at the left edge of higher-level prosodic boundaries tend to be more forcefully articulated than those at lower-level boundaries, a phenomenon known as domain-initial strengthening. This study tests whether similar effects occur in Turkish, using the Autosegmental-Metrical model proposed by Ipek & Jun [1, 2] as the basis for assessing boundary strength. Productions of /t/ and /d/ were elicited in four domain-initial prosodic positions corresponding to progressively higher-level boundaries: syllable, word, intermediate phrase, and Intonational Phrase. A fifth position, nuclear word, was included in order to better situate it within the prosodic hierarchy. Acoustic correlates of articulatory strength were measured, including closure duration for /d/ and /t/, as well as voice onset time and burst energy for /t/. Our results show that closure duration increases cumulatively from syllable to intermediate phrase, while voice onset time and burst energy are not influenced by boundary strength. These findings provide corroborating evidence for Ipek & Jun’s model, particularly for the distinction between word and intermediate phrase boundaries. Additionally, articulatory strength at the left edge of the nuclear word patterned closely with word-initial position, supporting the view that the nuclear word is not associated with a distinct phrasing domain
  • 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.
  • 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.
  • Crago, M. B., Allen, S. E. M., & Pesco, D. (1998). Issues of Complexity in Inuktitut and English Child Directed Speech. In Proceedings of the twenty-ninth Annual Stanford Child Language Research Forum (pp. 37-46).
  • 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.
  • 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.
  • Cutler, A., & Otake, T. (1998). Assimilation of place in Japanese and Dutch. In R. Mannell, & J. Robert-Ribes (Eds.), Proceedings of the Fifth International Conference on Spoken Language Processing: vol. 5 (pp. 1751-1754). Sydney: ICLSP.

    Abstract

    Assimilation of place of articulation across a nasal and a following stop consonant is obligatory in Japanese, but not in Dutch. In four experiments the processing of assimilated forms by speakers of Japanese and Dutch was compared, using a task in which listeners blended pseudo-word pairs such as ranga-serupa. An assimilated blend of this pair would be rampa, an unassimilated blend rangpa. Japanese listeners produced significantly more assimilated than unassimilated forms, both with pseudo-Japanese and pseudo-Dutch materials, while Dutch listeners produced significantly more unassimilated than assimilated forms in each materials set. This suggests that Japanese listeners, whose native-language phonology involves obligatory assimilation constraints, represent the assimilated nasals in nasal-stop sequences as unmarked for place of articulation, while Dutch listeners, who are accustomed to hearing unassimilated forms, represent the same nasal segments as marked for place of articulation.
  • 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.
  • Cutler, A. (1994). How human speech recognition is affected by phonological diversity among languages. In R. Togneri (Ed.), Proceedings of the fifth Australian International Conference on Speech Science and Technology: Vol. 1 (pp. 285-288). Canberra: Australian Speech Science and Technology Association.

    Abstract

    Listeners process spoken language in ways which are adapted to the phonological structure of their native language. As a consequence, non-native speakers do not listen to a language in the same way as native speakers; moreover, listeners may use their native language listening procedures inappropriately with foreign input. With sufficient experience, however, it may be possible to inhibit this latter (counter-productive) behavior.
  • Cutler, A. (1998). How listeners find the right words. In Proceedings of the Sixteenth International Congress on Acoustics: Vol. 2 (pp. 1377-1380). Melville, NY: Acoustical Society of America.

    Abstract

    Languages contain tens of thousands of words, but these are constructed from a tiny handful of phonetic elements. Consequently, words resemble one another, or can be embedded within one another, a coup stick snot with standing. me process of spoken-word recognition by human listeners involves activation of multiple word candidates consistent with the input, and direct competition between activated candidate words. Further, human listeners are sensitive, at an early, prelexical, stage of speeeh processing, to constraints on what could potentially be a word of the language.
  • Cutler, A., Treiman, R., & Van Ooijen, B. (1998). Orthografik inkoncistensy ephekts in foneme detektion? In R. Mannell, & J. Robert-Ribes (Eds.), Proceedings of the Fifth International Conference on Spoken Language Processing: Vol. 6 (pp. 2783-2786). Sydney: ICSLP.

    Abstract

    The phoneme detection task is widely used in spoken word recognition research. Alphabetically literate participants, however, are more used to explicit representations of letters than of phonemes. The present study explored whether phoneme detection is sensitive to how target phonemes are, or may be, orthographically realised. Listeners detected the target sounds [b,m,t,f,s,k] in word-initial position in sequences of isolated English words. Response times were faster to the targets [b,m,t], which have consistent word-initial spelling, than to the targets [f,s,k], which are inconsistently spelled, but only when listeners’ attention was drawn to spelling by the presence in the experiment of many irregularly spelled fillers. Within the inconsistent targets [f,s,k], there was no significant difference between responses to targets in words with majority and minority spellings. We conclude that performance in the phoneme detection task is not necessarily sensitive to orthographic effects, but that salient orthographic manipulation can induce such sensitivity.
  • Cutler, A., & Koster, M. (2000). Stress and lexical activation in Dutch. In B. Yuan, T. Huang, & X. Tang (Eds.), Proceedings of the Sixth International Conference on Spoken Language Processing: Vol. 1 (pp. 593-596). Beijing: China Military Friendship Publish.

    Abstract

    Dutch listeners were slower to make judgements about the semantic relatedness between a spoken target word (e.g. atLEET, 'athlete') and a previously presented visual prime word (e.g. SPORT 'sport') when the spoken word was mis-stressed. The adverse effect of mis-stressing confirms the role of stress information in lexical recognition in Dutch. However, although the erroneous stress pattern was always initially compatible with a competing word (e.g. ATlas, 'atlas'), mis-stressed words did not produced high false alarm rates in unrelated pairs (e.g. SPORT - atLAS). This suggests that stress information did not completely rule out segmentally matching but suprasegmentally mismatching words, a finding consistent with spoken-word recognition models involving multiple activation and inter-word competition.
  • Cutler, A., & Young, D. (1994). Rhythmic structure of word blends in English. In Proceedings of the Third International Conference on Spoken Language Processing (pp. 1407-1410). Kobe: Acoustical Society of Japan.

    Abstract

    Word blends combine fragments from two words, either in speech errors or when a new word is created. Previous work has demonstrated that in Japanese, such blends preserve moraic structure; in English they do not. A similar effect of moraic structure is observed in perceptual research on segmentation of continuous speech in Japanese; English listeners, by contrast, exploit stress units in segmentation, suggesting that a general rhythmic constraint may underlie both findings. The present study examined whether mis parallel would also hold for word blends. In spontaneous English polysyllabic blends, the source words were significantly more likely to be split before a strong than before a weak (unstressed) syllable, i.e. to be split at a stress unit boundary. In an experiment in which listeners were asked to identify the source words of blends, significantly more correct detections resulted when splits had been made before strong syllables. Word blending, like speech segmentation, appears to be constrained by language rhythm.
  • Cutler, A. (1998). The recognition of spoken words with variable representations. In D. Duez (Ed.), Proceedings of the ESCA Workshop on Sound Patterns of Spontaneous Speech (pp. 83-92). Aix-en-Provence: Université de Aix-en-Provence.
  • Cutler, A., McQueen, J. M., Baayen, R. H., & Drexler, H. (1994). Words within words in a real-speech corpus. In R. Togneri (Ed.), Proceedings of the 5th Australian International Conference on Speech Science and Technology: Vol. 1 (pp. 362-367). Canberra: Australian Speech Science and Technology Association.

    Abstract

    In a 50,000-word corpus of spoken British English the occurrence of words embedded within other words is reported. Within-word embedding in this real speech sample is common, and analogous to the extent of embedding observed in the vocabulary. Imposition of a syllable boundary matching constraint reduces but by no means eliminates spurious embedding. Embedded words are most likely to overlap with the beginning of matrix words, and thus may pose serious problems for speech recognisers.
  • Cutler, A., Norris, D., & McQueen, J. M. (2000). Tracking TRACE’s troubles. In A. Cutler, J. M. McQueen, & R. Zondervan (Eds.), Proceedings of SWAP (Workshop on Spoken Word Access Processes) (pp. 63-66). Nijmegen: Max-Planck-Institute for Psycholinguistics.

    Abstract

    Simulations explored the inability of the TRACE model of spoken-word recognition to model the effects on human listening of acoustic-phonetic mismatches in word forms. The source of TRACE's failure lay not in its interactive connectivity, not in the presence of interword competition, and not in the use of phonemic representations, but in the need for continuously optimised interpretation of the input. When an analogue of TRACE was allowed to cycle to asymptote on every slice of input, an acceptable simulation of the subcategorical mismatch data was achieved. Even then, however, the simulation was not as close as that produced by the Merge model.
  • 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.
  • Drozd, K. F. (1998). No as a determiner in child English: A summary of categorical evidence. In A. Sorace, C. Heycock, & R. Shillcock (Eds.), Proceedings of the Gala '97 Conference on Language Acquisition (pp. 34-39). Edinburgh, UK: Edinburgh University Press,.

    Abstract

    This paper summarizes the results of a descriptive syntactic category analysis of child English no which reveals that young children use and represent no as a determiner and negatives like no pen as NPs, contra standard analyses.
  • 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.
  • Enfield, N. J., & Evans, G. (2000). Transcription as standardisation: The problem of Tai languages. In S. Burusphat (Ed.), Proceedings: the International Conference on Tai Studies, July 29-31, 1998, (pp. 201-212). Bangkok, Thailand: Institute of Language and Culture for Rural Development, Mahidol University.
  • 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.
  • 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.
  • Falk, J. J., Zhang, Y., Scheutz, M., & Yu, C. (2021). Parents adaptively use anaphora during parent-child social interaction. 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. 1472-1478). Vienna: Cognitive Science Society.

    Abstract

    Anaphora, a ubiquitous feature of natural language, poses a particular challenge to young children as they first learn language due to its referential ambiguity. In spite of this, parents and caregivers use anaphora frequently in child-directed speech, potentially presenting a risk to effective communication if children do not yet have the linguistic capabilities of resolving anaphora successfully. Through an eye-tracking study in a naturalistic free-play context, we examine the strategies that parents employ to calibrate their use of anaphora to their child's linguistic development level. We show that, in this way, parents are able to intuitively scaffold the complexity of their speech such that greater referential ambiguity does not hurt overall communication success.
  • 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.
  • 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., 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., 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.
  • 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.
  • Gussenhoven, C., & Chen, A. (2000). Universal and language-specific effects in the perception of question intonation. In B. Yuan, T. Huang, & X. Tang (Eds.), Proceedings of the 6th International Conference on Spoken Language Processing (ICSLP) (pp. 91-94). Beijing: China Military Friendship Publish.

    Abstract

    Three groups of monolingual listeners, with Standard Chinese, Dutch and Hungarian as their native language, judged pairs of trisyllabic stimuli which differed only in their itch pattern. The segmental structure of the stimuli was made up by the experimenters and presented to subjects as being taken from a little-known language spoken on a South Pacific island. Pitch patterns consisted of a single rise-fall located on or near the second syllable. By and large, listeners selected the stimulus with the higher peak, the later eak, and the higher end rise as the one that signalled a question, regardless of language group. The result is argued to reflect innate, non-linguistic knowledge of the meaning of pitch variation, notably Ohala’s Frequency Code. A significant difference between groups is explained as due to the influence of the mother tongue.
  • Gussenhoven, C., & Chen, A. (2000). Universal and language-specific effects in the perception of question intonation. In Proceedings of the 6th International Conference on Spoken Language Processing (ICSLP) (pp. 91-94).
  • Harbusch, K., & Kempen, G. (2000). Complexity of linear order computation in Performance Grammar, TAG and HPSG. In Proceedings of Fifth International Workshop on Tree Adjoining Grammars and Related Formalisms (TAG+5) (pp. 101-106).

    Abstract

    This paper investigates the time and space complexity of word order computation in the psycholinguistically motivated grammar formalism of Performance Grammar (PG). In PG, the first stage of syntax assembly yields an unordered tree ('mobile') consisting of a hierarchy of lexical frames (lexically anchored elementary trees). Associated with each lexica l frame is a linearizer—a Finite-State Automaton that locally computes the left-to-right order of the branches of the frame. Linearization takes place after the promotion component may have raised certain constituents (e.g. Wh- or focused phrases) into the domain of lexical frames higher up in the syntactic mobile. We show that the worst-case time and space complexity of analyzing input strings of length n is O(n5) and O(n4), respectively. This result compares favorably with the time complexity of word-order computations in Tree Adjoining Grammar (TAG). A comparison with Head-Driven Phrase Structure Grammar (HPSG) reveals that PG yields a more declarative linearization method, provided that the FSA is rewritten as an equivalent regular expression.
  • Harmon, Z., Barak, L., Shafto, P., Edwards, J., & Feldman, N. H. (2021). Making heads or tails of it: A competition–compensation account of morphological deficits in language impairment. 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. 1872-1878). Vienna: Cognitive Science Society.

    Abstract

    Children with developmental language disorder (DLD) regularly use the base form of verbs (e.g., dance) instead of inflected forms (e.g., danced). We propose an account of this behavior in which children with DLD have difficulty processing novel inflected verbs in their input. This leads the inflected form to face stronger competition from alternatives. Competition is resolved by the production of a more accessible alternative with high semantic overlap with the inflected form: in English, the bare form. We test our account computationally by training a nonparametric Bayesian model that infers the productivity of the inflectional suffix (-ed). We systematically vary the number of novel types of inflected verbs in the input to simulate the input as processed by children with and without DLD. Modeling results are consistent with our hypothesis, suggesting that children’s inconsistent use of inflectional morphemes could stem from inferences they make on the basis of impoverished data.
  • 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
  • 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.
  • Janse, E., Sennema, A., & Slis, A. (2000). Fast speech timing in Dutch: The durational correlates of lexical stress and pitch accent. In Proceedings of the VIth International Conference on Spoken Language Processing, Vol. III (pp. 251-254).

    Abstract

    n this study we investigated the durational correlates of lexical stress and pitch accent at normal and fast speech rate in Dutch. Previous literature on English shows that durations of lexically unstressed vowels are reduced more than stressed vowels when speakers increase their speech rate. We found that the same holds for Dutch, irrespective of whether the unstressed vowel is schwa or a "full" vowel. In the same line, we expected that vowels in words without a pitch accent would be shortened relatively more than vowels in words with a pitch accent. This was not the case: if anything, the accented vowels were shortened relatively more than the unaccented vowels. We conclude that duration is an important cue for lexical stress, but not for pitch accent.
  • Janse, E. (2000). Intelligibility of time-compressed speech: Three ways of time-compression. In Proceedings of the VIth International Conference on Spoken Language Processing, vol. III (pp. 786-789).

    Abstract

    Studies on fast speech have shown that word-level timing of fast speech differs from that of normal rate speech in that unstressed syllables are shortened more than stressed syllables as speech rate increases. An earlier experiment showed that the intelligibility of time-compressed speech could not be improved by making its temporal organisation closer to natural fast speech. To test the hypothesis that segmental intelligibility is more important than prosodic timing in listening to timecompressed speech, the intelligibility of bisyllabic words was tested in three time-compression conditions: either stressed and unstressed syllable were compressed to the same degree, or the stressed syllable was compressed more than the unstressed syllable, or the reverse. As was found before, imitating wordlevel timing of fast speech did not improve intelligibility over linear compression. However, the results did not confirm the hypothesis either: there was no difference in intelligibility between the three compression conditions. We conclude that segmental intelligibility plays an important role, but further research is necessary to decide between the contributions of prosody and segmental intelligibility to the word-level intelligibility of time-compressed speech.
  • Janssen, R., Moisik, S. R., & Dediu, D. (2018). Agent model reveals the influence of vocal tract anatomy on speech during ontogeny and glossogeny. 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. 171-174). Toruń, Poland: NCU Press. doi:10.12775/3991-1.042.
  • Johnson, E. K., Jusczyk, P. W., Cutler, A., & Norris, D. (2000). The development of word recognition: The use of the possible-word constraint by 12-month-olds. In L. Gleitman, & A. Joshi (Eds.), Proceedings of CogSci 2000 (pp. 1034). London: Erlbaum.
  • Kanero, J., Franko, I., Oranç, C., Uluşahin, O., Koskulu, S., Adigüzel, Z., Küntay, A. C., & Göksun, T. (2018). Who can benefit from robots? Effects of individual differences in robot-assisted language learning. In Proceedings of the 8th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) (pp. 212-217). Piscataway, NJ, USA: IEEE.

    Abstract

    It has been suggested that some individuals may benefit more from social robots than do others. Using second
    language (L2) as an example, the present study examined how individual differences in attitudes toward robots and personality
    traits may be related to learning outcomes. Preliminary results with 24 Turkish-speaking adults suggest that negative attitudes
    toward robots, more specifically thoughts and anxiety about the negative social impact that robots may have on the society,
    predicted how well adults learned L2 words from a social robot. The possible implications of the findings as well as future directions are also discussed
  • 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.
  • Kempen, G., & Harbusch, K. (1998). A 'tree adjoining' grammar without adjoining: The case of scrambling in German. In Fourth International Workshop on Tree Adjoining Grammars and Related Frameworks (TAG+4).
  • Kempen, G., & Hoenkamp, E. (1982). Incremental sentence generation: Implications for the structure of a syntactic processor. In J. Horecký (Ed.), COLING 82. Proceedings of the Ninth International Conference on Computational Linguistics, Prague, July 5-10, 1982 (pp. 151-156). Amsterdam: North-Holland.

    Abstract

    Human speakers often produce sentences incrementally. They can start speaking having in mind only a fragmentary idea of what they want to say, and while saying this they refine the contents underlying subsequent parts of the utterance. This capability imposes a number of constraints on the design of a syntactic processor. This paper explores these constraints and evaluates some recent computational sentence generators from the perspective of incremental production.
  • Kempen, G. (1994). Innovative language checking software for Dutch. In J. Van Gent, & E. Peeters (Eds.), Proceedings of the 2e Dag van het Document (pp. 99-100). Delft: TNO Technisch Physische Dienst.
  • Kempen, G. (1994). The unification space: A hybrid model of human syntactic processing [Abstract]. In Cuny 1994 - The 7th Annual CUNY Conference on Human Sentence Processing. March 17-19, 1994. CUNY Graduate Center, New York.
  • Kempen, G., & Dijkstra, A. (1994). Toward an integrated system for grammar, writing and spelling instruction. In L. Appelo, & F. De Jong (Eds.), Computer-Assisted Language Learning: Proceedings of the Seventh Twente Workshop on Language Technology (pp. 41-46). Enschede: University of Twente.
  • Kita, S., van Gijn, I., & van der Hulst, H. (1998). Movement phases in signs and co-speech gestures, and their transcription by human coders. In Gesture and Sign-Language in Human-Computer Interaction (Lecture Notes in Artificial Intelligence - LNCS Subseries, Vol. 1371) (pp. 23-35). Berlin, Germany: Springer-Verlag.

    Abstract

    The previous literature has suggested that the hand movement in co-speech gestures and signs consists of a series of phases with qualitatively different dynamic characteristics. In this paper, we propose a syntagmatic rule system for movement phases that applies to both co-speech gestures and signs. Descriptive criteria for the rule system were developed for the analysis video-recorded continuous production of signs and gesture. It involves segmenting a stream of body movement into phases and identifying different phase types. Two human coders used the criteria to analyze signs and cospeech gestures that are produced in natural discourse. It was found that the criteria yielded good inter-coder reliability. These criteria can be used for the technology of automatic recognition of signs and co-speech gestures in order to segment continuous production and identify the potentially meaningbearing phase.
  • Klein, W. (2000). Changing concepts of the nature-nurture debate. In R. Hide, J. Mittelstrass, & W. Singer (Eds.), Changing concepts of nature at the turn of the millenium: Proceedings plenary session of the Pontifical academy of sciences, 26-29 October 1998 (pp. 289-299). Vatican City: Pontificia Academia Scientiarum.
  • Klein, W., & Dittmar, N. (Eds.). (1994). Interkulturelle Kommunikation [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (93).
  • Klein, W. (Ed.). (1998). Kaleidoskop [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (112).
  • Klein, W. (Ed.). (2000). Sprache des Rechts [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (118).
  • Klein, W. (Ed.). (1985). Schriftlichkeit [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (59).
  • Klein, W. (Ed.). (1982). Zweitspracherwerb [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (45).
  • Koutamanis, E., Kootstra, G. J., Dijkstra, T., & Unsworth., S. (2021). Lexical priming as evidence for language-nonselective access in the simultaneous bilingual child's lexicon. In D. Dionne, & L.-A. Vidal Covas (Eds.), BUCLD 45: Proceedings of the 45th annual Boston University Conference on Language Development (pp. 413-430). Sommerville, MA: Cascadilla Press.
  • Lansner, A., Sandberg, A., Petersson, K. M., & Ingvar, M. (2000). On forgetful attractor network memories. In H. Malmgren, M. Borga, & L. Niklasson (Eds.), Artificial neural networks in medicine and biology: Proceedings of the ANNIMAB-1 Conference, Göteborg, Sweden, 13-16 May 2000 (pp. 54-62). Heidelberg: Springer Verlag.

    Abstract

    A recurrently connected attractor neural network with a Hebbian learning rule is currently our best ANN analogy for a piece cortex. Functionally biological memory operates on a spectrum of time scales with regard to induction and retention, and it is modulated in complex ways by sub-cortical neuromodulatory systems. Moreover, biological memory networks are commonly believed to be highly distributed and engage many co-operating cortical areas. Here we focus on the temporal aspects of induction and retention of memory in a connectionist type attractor memory model of a piece of cortex. A continuous time, forgetful Bayesian-Hebbian learning rule is described and compared to the characteristics of LTP and LTD seen experimentally. More generally, an attractor network implementing this learning rule can operate as a long-term, intermediate-term, or short-term memory. Modulation of the print-now signal of the learning rule replicates some experimental memory phenomena, like e.g. the von Restorff effect.
  • Lattenkamp, E. Z., Vernes, S. C., & Wiegrebe, L. (2018). Mammalian models for the study of vocal learning: A new paradigm in bats. 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. 235-237). Toruń, Poland: NCU Press. doi:10.12775/3991-1.056.
  • Lauscher, A., Eckert, K., Galke, L., Scherp, A., Rizvi, S. T. R., Ahmed, S., Dengel, A., Zumstein, P., & Klein, A. (2018). Linked open citation database: Enabling libraries to contribute to an open and interconnected citation graph. In J. Chen, M. A. Gonçalves, J. M. Allen, E. A. Fox, M.-Y. Kan, & V. Petras (Eds.), JCDL '18: Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries (pp. 109-118). New York: ACM. doi:10.1145/3197026.3197050.

    Abstract

    Citations play a crucial role in the scientific discourse, in information retrieval, and in bibliometrics. Many initiatives are currently promoting the idea of having free and open citation data. Creation of citation data, however, is not part of the cataloging workflow in libraries nowadays.
    In this paper, we present our project Linked Open Citation Database, in which we design distributed processes and a system infrastructure based on linked data technology. The goal is to show that efficiently cataloging citations in libraries using a semi-automatic approach is possible. We specifically describe the current state of the workflow and its implementation. We show that we could significantly improve the automatic reference extraction that is crucial for the subsequent data curation. We further give insights on the curation and linking process and provide evaluation results that not only direct the further development of the project, but also allow us to discuss its overall feasibility.
  • Lefever, E., Hendrickx, I., Croijmans, I., Van den Bosch, A., & Majid, A. (2018). Discovering the language of wine reviews: A text mining account. In N. Calzolari, K. Choukri, C. Cieri, T. Declerck, S. Goggi, K. Hasida, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk, S. Piperidis, & T. Tokunaga (Eds.), Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018) (pp. 3297-3302). Paris: LREC.

    Abstract

    It is widely held that smells and flavors are impossible to put into words. In this paper we test this claim by seeking predictive patterns in wine reviews, which ostensibly aim to provide guides to perceptual content. Wine reviews have previously been critiqued as random and meaningless. We collected an English corpus of wine reviews with their structured metadata, and applied machine learning techniques to automatically predict the wine's color, grape variety, and country of origin. To train the three supervised classifiers, three different information sources were incorporated: lexical bag-of-words features, domain-specific terminology features, and semantic word embedding features. In addition, using regression analysis we investigated basic review properties, i.e., review length, average word length, and their relationship to the scalar values of price and review score. Our results show that wine experts do share a common vocabulary to describe wines and they use this in a consistent way, which makes it possible to automatically predict wine characteristics based on the review text alone. This means that odors and flavors may be more expressible in language than typically acknowledged.
  • Levelt, W. J. M., & Plomp, R. (1962). Musical consonance and critical bandwidth. In Proceedings of the 4th International Congress Acoustics (pp. 55-55).
  • Levelt, W. J. M. (1994). On the skill of speaking: How do we access words? In Proceedings ICSLP 94 (pp. 2253-2258). Yokohama: The Acoustical Society of Japan.
  • Levelt, W. J. M. (1994). Onder woorden brengen: Beschouwingen over het spreekproces. In Haarlemse voordrachten: voordrachten gehouden in de Hollandsche Maatschappij der Wetenschappen te Haarlem. Haarlem: Hollandsche maatschappij der wetenschappen.
  • Levelt, W. J. M. (1994). What can a theory of normal speaking contribute to AAC? In ISAAC '94 Conference Book and Proceedings. Hoensbroek: IRV.
  • Levinson, S. C. (2000). Language as nature and language as art. In J. Mittelstrass, & W. Singer (Eds.), Proceedings of the Symposium on ‘Changing concepts of nature and the turn of the Millennium (pp. 257-287). Vatican City: Pontificae Academiae Scientiarium Scripta Varia.
  • Levinson, S. C. (2000). H.P. Grice on location on Rossel Island. In S. S. Chang, L. Liaw, & J. Ruppenhofer (Eds.), Proceedings of the 25th Annual Meeting of the Berkeley Linguistic Society (pp. 210-224). Berkeley: Berkeley Linguistic Society.
  • Levinson, S. C., & Haviland, J. B. (Eds.). (1994). Space in Mayan languages [Special Issue]. Linguistics, 32(4/5).
  • Levshina, N., & Moran, S. (Eds.). (2021). Efficiency in human languages: Corpus evidence for universal principles [Special Issue]. Linguistics Vanguard, 7(s3).
  • Lopopolo, A., Frank, S. L., Van den Bosch, A., Nijhof, A., & Willems, R. M. (2018). The Narrative Brain Dataset (NBD), an fMRI dataset for the study of natural language processing in the brain. In B. Devereux, E. Shutova, & C.-R. Huang (Eds.), Proceedings of LREC 2018 Workshop "Linguistic and Neuro-Cognitive Resources (LiNCR) (pp. 8-11). Paris: LREC.

    Abstract

    We present the Narrative Brain Dataset, an fMRI dataset that was collected during spoken presentation of short excerpts of three
    stories in Dutch. Together with the brain imaging data, the dataset contains the written versions of the stimulation texts. The texts are
    accompanied with stochastic (perplexity and entropy) and semantic computational linguistic measures. The richness and unconstrained
    nature of the data allows the study of language processing in the brain in a more naturalistic setting than is common for fMRI studies.
    We hope that by making NBD available we serve the double purpose of providing useful neural data to researchers interested in natural
    language processing in the brain and to further stimulate data sharing in the field of neuroscience of language.
  • Lupyan, G., Wendorf, A., Berscia, L. M., & Paul, J. (2018). Core knowledge or language-augmented cognition? The case of geometric reasoning. 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. 252-254). Toruń, Poland: NCU Press. doi:10.12775/3991-1.062.
  • Mai, F., Galke, L., & Scherp, A. (2018). Using deep learning for title-based semantic subject indexing to reach competitive performance to full-text. In J. Chen, M. A. Gonçalves, J. M. Allen, E. A. Fox, M.-Y. Kan, & V. Petras (Eds.), JCDL '18: Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries (pp. 169-178). New York: ACM.

    Abstract

    For (semi-)automated subject indexing systems in digital libraries, it is often more practical to use metadata such as the title of a publication instead of the full-text or the abstract. Therefore, it is desirable to have good text mining and text classification algorithms that operate well already on the title of a publication. So far, the classification performance on titles is not competitive with the performance on the full-texts if the same number of training samples is used for training. However, it is much easier to obtain title data in large quantities and to use it for training than full-text data. In this paper, we investigate the question how models obtained from training on increasing amounts of title training data compare to models from training on a constant number of full-texts. We evaluate this question on a large-scale dataset from the medical domain (PubMed) and from economics (EconBiz). In these datasets, the titles and annotations of millions of publications are available, and they outnumber the available full-texts by a factor of 20 and 15, respectively. To exploit these large amounts of data to their full potential, we develop three strong deep learning classifiers and evaluate their performance on the two datasets. The results are promising. On the EconBiz dataset, all three classifiers outperform their full-text counterparts by a large margin. The best title-based classifier outperforms the best full-text method by 9.4%. On the PubMed dataset, the best title-based method almost reaches the performance of the best full-text classifier, with a difference of only 2.9%.
  • 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.
  • McQueen, J. M., & Cutler, A. (1998). Spotting (different kinds of) words in (different kinds of) context. In R. Mannell, & J. Robert-Ribes (Eds.), Proceedings of the Fifth International Conference on Spoken Language Processing: Vol. 6 (pp. 2791-2794). Sydney: ICSLP.

    Abstract

    The results of a word-spotting experiment are presented in which Dutch listeners tried to spot different types of bisyllabic Dutch words embedded in different types of nonsense contexts. Embedded verbs were not reliably harder to spot than embedded nouns; this suggests that nouns and verbs are recognised via the same basic processes. Iambic words were no harder to spot than trochaic words, suggesting that trochaic words are not in principle easier to recognise than iambic words. Words were harder to spot in consonantal contexts (i.e., contexts which themselves could not be words) than in longer contexts which contained at least one vowel (i.e., contexts which, though not words, were possible words of Dutch). A control experiment showed that this difference was not due to acoustic differences between the words in each context. The results support the claim that spoken-word recognition is sensitive to the viability of sound sequences as possible words.
  • McQueen, J. M., Cutler, A., & Norris, D. (2000). Positive and negative influences of the lexicon on phonemic decision-making. In B. Yuan, T. Huang, & X. Tang (Eds.), Proceedings of the Sixth International Conference on Spoken Language Processing: Vol. 3 (pp. 778-781). Beijing: China Military Friendship Publish.

    Abstract

    Lexical knowledge influences how human listeners make decisions about speech sounds. Positive lexical effects (faster responses to target sounds in words than in nonwords) are robust across several laboratory tasks, while negative effects (slower responses to targets in more word-like nonwords than in less word-like nonwords) have been found in phonetic decision tasks but not phoneme monitoring tasks. The present experiments tested whether negative lexical effects are therefore a task-specific consequence of the forced choice required in phonetic decision. We compared phoneme monitoring and phonetic decision performance using the same Dutch materials in each task. In both experiments there were positive lexical effects, but no negative lexical effects. We observe that in all studies showing negative lexical effects, the materials were made by cross-splicing, which meant that they contained perceptual evidence supporting the lexically-consistent phonemes. Lexical knowledge seems to influence phonemic decision-making only when there is evidence for the lexically-consistent phoneme in the speech signal.
  • McQueen, J. M., Cutler, A., & Norris, D. (2000). Why Merge really is autonomous and parsimonious. In A. Cutler, J. M. McQueen, & R. Zondervan (Eds.), Proceedings of SWAP (Workshop on Spoken Word Access Processes) (pp. 47-50). Nijmegen: Max-Planck-Institute for Psycholinguistics.

    Abstract

    We briefly describe the Merge model of phonemic decision-making, and, in the light of general arguments about the possible role of feedback in spoken-word recognition, defend Merge's feedforward structure. Merge not only accounts adequately for the data, without invoking feedback connections, but does so in a parsimonious manner.
  • Merkx, D., & Frank, S. L. (2021). Human sentence processing: Recurrence or attention? In E. Chersoni, N. Hollenstein, C. Jacobs, Y. Oseki, L. Prévot, & E. Santus (Eds.), Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics (CMCL 2021) (pp. 12-22). Stroudsburg, PA, USA: Association for Computational Linguistics (ACL). doi:10.18653/v1/2021.cmcl-1.2.

    Abstract

    Recurrent neural networks (RNNs) have long been an architecture of interest for computational models of human sentence processing. The recently introduced Transformer architecture outperforms RNNs on many natural language processing tasks but little is known about its ability to model human language processing. We compare Transformer- and RNN-based language models’ ability to account for measures of human reading effort. Our analysis shows Transformers to outperform RNNs in explaining self-paced reading times and neural activity during reading English sentences, challenging the widely held idea that human sentence processing involves recurrent and immediate processing and provides evidence for cue-based retrieval.
  • Merkx, D., Frank, S. L., & Ernestus, M. (2021). Semantic sentence similarity: Size does not always matter. In Proceedings of Interspeech 2021 (pp. 4393-4397). doi:10.21437/Interspeech.2021-1464.

    Abstract

    This study addresses the question whether visually grounded speech recognition (VGS) models learn to capture sentence semantics without access to any prior linguistic knowledge. We produce synthetic and natural spoken versions of a well known semantic textual similarity database and show that our VGS model produces embeddings that correlate well with human semantic similarity judgements. Our results show that a model trained on a small image-caption database outperforms two models trained on much larger databases, indicating that database size is not all that matters. We also investigate the importance of having multiple captions per image and find that this is indeed helpful even if the total number of images is lower, suggesting that paraphrasing is a valuable learning signal. While the general trend in the field is to create ever larger datasets to train models on, our findings indicate other characteristics of the database can just as important.
  • Merkx, D., & Scharenborg, O. (2018). Articulatory feature classification using convolutional neural networks. In Proceedings of Interspeech 2018 (pp. 2142-2146). doi:10.21437/Interspeech.2018-2275.

    Abstract

    The ultimate goal of our research is to improve an existing speech-based computational model of human speech recognition on the task of simulating the role of fine-grained phonetic information in human speech processing. As part of this work we are investigating articulatory feature classifiers that are able to create reliable and accurate transcriptions of the articulatory behaviour encoded in the acoustic speech signal. Articulatory feature (AF) modelling of speech has received a considerable amount of attention in automatic speech recognition research. Different approaches have been used to build AF classifiers, most notably multi-layer perceptrons. Recently, deep neural networks have been applied to the task of AF classification. This paper aims to improve AF classification by investigating two different approaches: 1) investigating the usefulness of a deep Convolutional neural network (CNN) for AF classification; 2) integrating the Mel filtering operation into the CNN architecture. The results showed a remarkable improvement in classification accuracy of the CNNs over state-of-the-art AF classification results for Dutch, most notably in the minority classes. Integrating the Mel filtering operation into the CNN architecture did not further improve classification performance.
  • Micklos, A., Macuch Silva, V., & Fay, N. (2018). The prevalence of repair in studies of language evolution. 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. 316-318). Toruń, Poland: NCU Press. doi:10.12775/3991-1.075.
  • 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.
  • Mulder, K., Ten Bosch, L., & Boves, L. (2018). Analyzing EEG Signals in Auditory Speech Comprehension Using Temporal Response Functions and Generalized Additive Models. In Proceedings of Interspeech 2018 (pp. 1452-1456). doi:10.21437/Interspeech.2018-1676.

    Abstract

    Analyzing EEG signals recorded while participants are listening to continuous speech with the purpose of testing linguistic hypotheses is complicated by the fact that the signals simultaneously reflect exogenous acoustic excitation and endogenous linguistic processing. This makes it difficult to trace subtle differences that occur in mid-sentence position. We apply an analysis based on multivariate temporal response functions to uncover subtle mid-sentence effects. This approach is based on a per-stimulus estimate of the response of the neural system to speech input. Analyzing EEG signals predicted on the basis of the response functions might then bring to light conditionspecific differences in the filtered signals. We validate this approach by means of an analysis of EEG signals recorded with isolated word stimuli. Then, we apply the validated method to the analysis of the responses to the same words in the middle of meaningful sentences.
  • Norris, D., McQueen, J. M., & Cutler, A. (1994). Competition and segmentation in spoken word recognition. In Proceedings of the Third International Conference on Spoken Language Processing: Vol. 1 (pp. 401-404). Yokohama: PACIFICO.

    Abstract

    This paper describes recent experimental evidence which shows that models of spoken word recognition must incorporate both inhibition between competing lexical candidates and a sensitivity to metrical cues to lexical segmentation. A new version of the Shortlist [1][2] model incorporating the Metrical Segmentation Strategy [3] provides a detailed simulation of the data.
  • Norris, D., Cutler, A., McQueen, J. M., Butterfield, S., & Kearns, R. K. (2000). Language-universal constraints on the segmentation of English. In A. Cutler, J. M. McQueen, & R. Zondervan (Eds.), Proceedings of SWAP (Workshop on Spoken Word Access Processes) (pp. 43-46). Nijmegen: Max-Planck-Institute for Psycholinguistics.

    Abstract

    Two word-spotting experiments are reported that examine whether the Possible-Word Constraint (PWC) [1] is a language-specific or language-universal strategy for the segmentation of continuous speech. The PWC disfavours parses which leave an impossible residue between the end of a candidate word and a known boundary. The experiments examined cases where the residue was either a CV syllable with a lax vowel, or a CVC syllable with a schwa. Although neither syllable context is a possible word in English, word-spotting in both contexts was easier than with a context consisting of a single consonant. The PWC appears to be language-universal rather than language-specific.
  • Norris, D., Cutler, A., & McQueen, J. M. (2000). The optimal architecture for simulating spoken-word recognition. In C. Davis, T. Van Gelder, & R. Wales (Eds.), Cognitive Science in Australia, 2000: Proceedings of the Fifth Biennial Conference of the Australasian Cognitive Science Society. Adelaide: Causal Productions.

    Abstract

    Simulations explored the inability of the TRACE model of spoken-word recognition to model the effects on human listening of subcategorical mismatch in word forms. The source of TRACE's failure lay not in interactive connectivity, not in the presence of inter-word competition, and not in the use of phonemic representations, but in the need for continuously optimised interpretation of the input. When an analogue of TRACE was allowed to cycle to asymptote on every slice of input, an acceptable simulation of the subcategorical mismatch data was achieved. Even then, however, the simulation was not as close as that produced by the Merge model, which has inter-word competition, phonemic representations and continuous optimisation (but no interactive connectivity).
  • Otake, T., & Cutler, A. (2000). A set of Japanese word cohorts rated for relative familiarity. In B. Yuan, T. Huang, & X. Tang (Eds.), Proceedings of the Sixth International Conference on Spoken Language Processing: Vol. 3 (pp. 766-769). Beijing: China Military Friendship Publish.

    Abstract

    A database is presented of relative familiarity ratings for 24 sets of Japanese words, each set comprising words overlapping in the initial portions. These ratings are useful for the generation of material sets for research in the recognition of spoken words.
  • Ozyurek, A. (1998). An analysis of the basic meaning of Turkish demonstratives in face-to-face conversational interaction. In S. Santi, I. Guaitella, C. Cave, & G. Konopczynski (Eds.), Oralite et gestualite: Communication multimodale, interaction: actes du colloque ORAGE 98 (pp. 609-614). Paris: L'Harmattan.
  • Ozyurek, A. (1994). How children talk about a conversation. In K. Beals, J. Denton, R. Knippen, L. Melnar, H. Suzuki, & E. Zeinfeld (Eds.), Papers from the Thirtieth Regional Meeting of the Chicago Linguistic Society: Main Session (pp. 309-319). Chicago, Ill: Chicago Linguistic Society.
  • Ozyurek, A. (1994). How children talk about conversations: Development of roles and voices. In E. V. Clark (Ed.), Proceedings of the Twenty-Sixth Annual Child Language Research Forum (pp. 197-206). Stanford: CSLI Publications.
  • Ozyurek, A., & Ozcaliskan, S. (2000). How do children learn to conflate manner and path in their speech and gestures? Differences in English and Turkish. In E. V. Clark (Ed.), The proceedings of the Thirtieth Child Language Research Forum (pp. 77-85). Stanford: CSLI Publications.
  • 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.
  • Räsänen, O., Seshadri, S., & Casillas, M. (2018). Comparison of syllabification algorithms and training strategies for robust word count estimation across different languages and recording conditions. In Proceedings of Interspeech 2018 (pp. 1200-1204). doi:10.21437/Interspeech.2018-1047.

    Abstract

    Word count estimation (WCE) from audio recordings has a number of applications, including quantifying the amount of speech that language-learning infants hear in their natural environments, as captured by daylong recordings made with devices worn by infants. To be applicable in a wide range of scenarios and also low-resource domains, WCE tools should be extremely robust against varying signal conditions and require minimal access to labeled training data in the target domain. For this purpose, earlier work has used automatic syllabification of speech, followed by a least-squares-mapping of syllables to word counts. This paper compares a number of previously proposed syllabifiers in the WCE task, including a supervised bi-directional long short-term memory (BLSTM) network that is trained on a language for which high quality syllable annotations are available (a “high resource language”), and reports how the alternative methods compare on different languages and signal conditions. We also explore additive noise and varying-channel data augmentation strategies for BLSTM training, and show how they improve performance in both matching and mismatching languages. Intriguingly, we also find that even though the BLSTM works on languages beyond its training data, the unsupervised algorithms can still outperform it in challenging signal conditions on novel languages.
  • Ravignani, A., Garcia, M., Gross, S., de Reus, K., Hoeksema, N., Rubio-Garcia, A., & de Boer, B. (2018). Pinnipeds have something to say about speech and rhythm. 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. 399-401). Toruń, Poland: NCU Press. doi:10.12775/3991-1.095.

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