Publications

Displaying 1 - 100 of 148
  • Alday, P. M. (2016). Towards a rigorous motivation for Ziph's law. In S. G. Roberts, C. Cuskley, L. McCrohon, L. Barceló-Coblijn, O. Feher, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11). Retrieved from http://evolang.org/neworleans/papers/178.html.

    Abstract

    Language evolution can be viewed from two viewpoints: the development of a communicative system and the biological adaptations necessary for producing and perceiving said system. The communicative-system vantage point has enjoyed a wealth of mathematical models based on simple distributional properties of language, often formulated as empirical laws. However, be- yond vague psychological notions of “least effort”, no principled explanation has been proposed for the existence and success of such laws. Meanwhile, psychological and neurobiological mod- els have focused largely on the computational constraints presented by incremental, real-time processing. In the following, we show that information-theoretic entropy underpins successful models of both types and provides a more principled motivation for Zipf’s Law
  • Alhama, R. G., & Zuidema, W. (2016). Generalization in Artificial Language Learning: Modelling the Propensity to Generalize. In Proceedings of the 7th Workshop on Cognitive Aspects of Computational Language Learning (pp. 64-72). Association for Computational Linguistics. doi:10.18653/v1/W16-1909.

    Abstract

    Experiments in Artificial Language Learn-
    ing have revealed much about the cogni-
    tive mechanisms underlying sequence and
    language learning in human adults, in in-
    fants and in non-human animals. This pa-
    per focuses on their ability to generalize
    to novel grammatical instances (i.e., in-
    stances consistent with a familiarization
    pattern). Notably, the propensity to gen-
    eralize appears to be negatively correlated
    with the amount of exposure to the artifi-
    cial language, a fact that has been claimed
    to be contrary to the predictions of statis-
    tical models (Pe
    ̃
    na et al. (2002); Endress
    and Bonatti (2007)). In this paper, we pro-
    pose to model generalization as a three-
    step process, and we demonstrate that the
    use of statistical models for the first two
    steps, contrary to widespread intuitions in
    the ALL-field, can explain the observed
    decrease of the propensity to generalize
    with exposure time.
  • Alhama, R. G., & Zuidema, W. (2016). Pre-Wiring and Pre-Training: What does a neural network need to learn truly general identity rules? In T. R. Besold, A. Bordes, & A. D'Avila Garcez (Eds.), CoCo 2016 Cognitive Computation: Proceedings of the Workshop on Cognitive Computation: Integrating neural and symbolic approaches 2016. CEUR Workshop Proceedings.

    Abstract

    In an influential paper, Marcus et al. [1999] claimed that connectionist models
    cannot account for human success at learning tasks that involved generalization
    of abstract knowledge such as grammatical rules. This claim triggered a heated
    debate, centered mostly around variants of the Simple Recurrent Network model
    [Elman, 1990]. In our work, we revisit this unresolved debate and analyze the
    underlying issues from a different perspective. We argue that, in order to simulate
    human-like learning of grammatical rules, a neural network model should not be
    used as a
    tabula rasa
    , but rather, the initial wiring of the neural connections and
    the experience acquired prior to the actual task should be incorporated into the
    model. We present two methods that aim to provide such initial state: a manipu-
    lation of the initial connections of the network in a cognitively plausible manner
    (concretely, by implementing a “delay-line” memory), and a pre-training algorithm
    that incrementally challenges the network with novel stimuli. We implement such
    techniques in an Echo State Network [Jaeger, 2001], and we show that only when
    combining both techniques the ESN is able to learn truly general identity rules.
  • 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.
  • Azar, Z., Backus, A., & Ozyurek, A. (2016). Pragmatic relativity: Gender and context affect the use of personal pronouns in discourse differentially across languages. In A. Papafragou, D. Grodner, D. Mirman, & J. Trueswell (Eds.), Proceedings of the 38th Annual Meeting of the Cognitive Science Society (CogSci 2016) (pp. 1295-1300). Austin, TX: Cognitive Science Society.

    Abstract

    Speakers use differential referring expressions in pragmatically appropriate ways to produce coherent narratives. Languages, however, differ in a) whether REs as arguments can be dropped and b) whether personal pronouns encode gender. We examine two languages that differ from each other in these two aspects and ask whether the co-reference context and the gender encoding options affect the use of REs differentially. We elicited narratives from Dutch and Turkish speakers about two types of three-person events, one including people of the same and the other of mixed-gender. Speakers re-introduced referents into the discourse with fuller forms (NPs) and maintained them with reduced forms (overt or null pronoun). Turkish speakers used pronouns mainly to mark emphasis and only Dutch speakers used pronouns differentially across the two types of videos. We argue that linguistic possibilities available in languages tune speakers into taking different principles into account to produce pragmatically coherent narratives
  • 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.
  • Bergmann, C., Cristia, A., & Dupoux, E. (2016). Discriminability of sound contrasts in the face of speaker variation quantified. In Proceedings of the 38th Annual Conference of the Cognitive Science Society. (pp. 1331-1336). Austin, TX: Cognitive Science Society.

    Abstract

    How does a naive language learner deal with speaker variation irrelevant to distinguishing word meanings? Experimental data is contradictory, and incompatible models have been proposed. Here, we examine basic assumptions regarding the acoustic signal the learner deals with: Is speaker variability a hurdle in discriminating sounds or can it easily be ignored? To this end, we summarize existing infant data. We then present machine-based discriminability scores of sound pairs obtained without any language knowledge. Our results show that speaker variability decreases sound contrast discriminability, and that some contrasts are affected more than others. However, chance performance is rare; most contrasts remain discriminable in the face of speaker variation. We take our results to mean that speaker variation is not a uniform hurdle to discriminating sound contrasts, and careful examination is necessary when planning and interpreting studies testing whether and to what extent infants (and adults) are sensitive to speaker differences.

    Additional information

    Scripts and data
  • 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
  • Bosker, H. R., Reinisch, E., & Sjerps, M. J. (2016). Listening under cognitive load makes speech sound fast. In H. van den Heuvel, B. Cranen, & S. Mattys (Eds.), Proceedings of the Speech Processing in Realistic Environments [SPIRE] Workshop (pp. 23-24). Groningen.
  • Bosker, H. R. (2016). Our own speech rate influences speech perception. In J. Barnes, A. Brugos, S. Stattuck-Hufnagel, & N. Veilleux (Eds.), Proceedings of Speech Prosody 2016 (pp. 227-231).

    Abstract

    During conversation, spoken utterances occur in rich acoustic contexts, including speech produced by our interlocutor(s) and speech we produced ourselves. Prosodic characteristics of the acoustic context have been known to influence speech perception in a contrastive fashion: for instance, a vowel presented in a fast context is perceived to have a longer duration than the same vowel in a slow context. Given the ubiquity of the sound of our own voice, it may be that our own speech rate - a common source of acoustic context - also influences our perception of the speech of others. Two experiments were designed to test this hypothesis. Experiment 1 replicated earlier contextual rate effects by showing that hearing pre-recorded fast or slow context sentences alters the perception of ambiguous Dutch target words. Experiment 2 then extended this finding by showing that talking at a fast or slow rate prior to the presentation of the target words also altered the perception of those words. These results suggest that between-talker variation in speech rate production may induce between-talker variation in speech perception, thus potentially explaining why interlocutors tend to converge on speech rate in dialogue settings.

    Additional information

    pdf via conference website227
  • Bowerman, M. (1996). Argument structure and learnability: Is a solution in sight? In J. Johnson, M. L. Juge, & J. L. Moxley (Eds.), Proceedings of the Twenty-second Annual Meeting of the Berkeley Linguistics Society, February 16-19, 1996. General Session and Parasession on The Role of Learnability in Grammatical Theory (pp. 454-468). Berkeley Linguistics Society.
  • 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.
  • Bruggeman, L., & Cutler, A. (2016). Lexical manipulation as a discovery tool for psycholinguistic research. In C. Carignan, & M. D. Tyler (Eds.), Proceedings of the 16th Australasian International Conference on Speech Science and Technology (SST2016) (pp. 313-316).
  • 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.
  • Croijmans, I., & Majid, A. (2016). Language does not explain the wine-specific memory advantage of wine experts. In A. Papafragou, D. Grodner, D. Mirman, & J. Trueswell (Eds.), Proceedings of the 38th Annual Meeting of the Cognitive Science Society (CogSci 2016) (pp. 141-146). Austin, TX: Cognitive Science Society.

    Abstract

    Although people are poor at naming odors, naming a smell helps to remember that odor. Previous studies show wine experts have better memory for smells, and they also name smells differently than novices. Is wine experts’ odor memory is verbally mediated? And is the odor memory advantage that experts have over novices restricted to odors in their domain of expertise, or does it generalize? Twenty-four wine experts and 24 novices smelled wines, wine-related odors and common odors, and remembered these. Half the participants also named the smells. Wine experts had better memory for wines, but not for the other odors, indicating their memory advantage is restricted to wine. Wine experts named odors better than novices, but there was no relationship between experts’ ability to name odors and their memory for odors. This suggests experts’ odor memory advantage is not linguistically mediated, but may be the result of differential perceptual learning
  • 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.
  • Ip, M., & Cutler, A. (2016). Cross-language data on five types of prosodic focus. In J. Barnes, A. Brugos, S. Shattuck-Hufnagel, & N. Veilleux (Eds.), Proceedings of Speech Prosody 2016 (pp. 330-334).

    Abstract

    To examine the relative roles of language-specific and language-universal mechanisms in the production of prosodic focus, we compared production of five different types of focus by native speakers of English and Mandarin. Two comparable dialogues were constructed for each language, with the same words appearing in focused and unfocused position; 24 speakers recorded each dialogue in each language. Duration, F0 (mean, maximum, range), and rms-intensity (mean, maximum) of all critical word tokens were measured. Across the different types of focus, cross-language differences were observed in the degree to which English versus Mandarin speakers use the different prosodic parameters to mark focus, suggesting that while prosody may be universally available for expressing focus, the means of its employment may be considerably language-specific
  • 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., & 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.
  • 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., & Otake, T. (1996). The processing of word prosody in Japanese. In P. McCormack, & A. Russell (Eds.), Proceedings of the 6th Australian International Conference on Speech Science and Technology (pp. 599-604). Canberra: Australian Speech Science and Technology Association.
  • Cutler, A. (1996). The comparative study of spoken-language processing. In H. T. Bunnell (Ed.), Proceedings of the Fourth International Conference on Spoken Language Processing: Vol. 1 (pp. 1). New York: Institute of Electrical and Electronics Engineers.

    Abstract

    Psycholinguists are saddled with a paradox. Their aim is to construct a model of human language processing, which will hold equally well for the processing of any language, but this aim cannot be achieved just by doing experiments in any language. They have to compare processing of many languages, and actively search for effects which are specific to a single language, even though a model which is itself specific to a single language is really the last thing they want.
  • 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., Aslin, R. N., Gervain, J., & Nespor, M. (Eds.). (2021). Special issue in honor of Jacques Mehler, Cognition's founding editor [Special Issue]. Cognition, 213.
  • Dediu, D., & Moisik, S. (2016). Defining and counting phonological classes in cross-linguistic segment databases. In N. Calzolari, K. Choukri, T. Declerck, S. Goggi, M. Grobelnik, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk, & S. Piperidis (Eds.), Proceedings of LREC 2016: 10th International Conference on Language Resources and Evaluation (pp. 1955-1962). Paris: European Language Resources Association (ELRA).

    Abstract

    Recently, there has been an explosion in the availability of large, good-quality cross-linguistic databases such as WALS (Dryer & Haspelmath, 2013), Glottolog (Hammarstrom et al., 2015) and Phoible (Moran & McCloy, 2014). Databases such as Phoible contain the actual segments used by various languages as they are given in the primary language descriptions. However, this segment-level representation cannot be used directly for analyses that require generalizations over classes of segments that share theoretically interesting features. Here we present a method and the associated R (R Core Team, 2014) code that allows the exible denition of such meaningful classes and that can identify the sets of segments falling into such a class for any language inventory. The method and its results are important for those interested in exploring cross-linguistic patterns of phonetic and phonological diversity and their relationship to extra-linguistic factors and processes such as climate, economics, history or human genetics.
  • Dediu, D., & Moisik, S. R. (2016). Anatomical biasing of click learning and production: An MRI and 3d palate imaging study. In S. G. Roberts, C. Cuskley, L. McCrohon, L. Barceló-Coblijn, O. Feher, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11). Retrieved from http://evolang.org/neworleans/papers/57.html.

    Abstract

    The current paper presents results for data on click learning obtained from a larger imaging study (using MRI and 3D intraoral scanning) designed to quantify and characterize intra- and inter-population variation of vocal tract structures and the relation of this to speech production. The aim of the click study was to ascertain whether and to what extent vocal tract morphology influences (1) the ability to learn to produce clicks and (2) the productions of those that successfully learn to produce these sounds. The results indicate that the presence of an alveolar ridge certainly does not prevent an individual from learning to produce click sounds (1). However, the subtle details of how clicks are produced may indeed be driven by palate shape (2).
  • 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.
  • Doumas, L. A., & Martin, A. E. (2016). Abstraction in time: Finding hierarchical linguistic structure in a model of relational processing. In A. Papafragou, D. Grodner, D. Mirman, & J. Trueswell (Eds.), Proceedings of the 38th Annual Meeting of the Cognitive Science Society (CogSci 2016) (pp. 2279-2284). Austin, TX: Cognitive Science Society.

    Abstract

    Abstract mental representation is fundamental for human cognition. Forming such representations in time, especially from dynamic and noisy perceptual input, is a challenge for any processing modality, but perhaps none so acutely as for language processing. We show that LISA (Hummel & Holyaok, 1997) and DORA (Doumas, Hummel, & Sandhofer, 2008), models built to process and to learn structured (i.e., symbolic) rep resentations of conceptual properties and relations from unstructured inputs, show oscillatory activation during processing that is highly similar to the cortical activity elicited by the linguistic stimuli from Ding et al.(2016). We argue, as Ding et al.(2016), that this activation reflects formation of hierarchical linguistic representation, and furthermore, that the kind of computational mechanisms in LISA/DORA (e.g., temporal binding by systematic asynchrony of firing) may underlie formation of abstract linguistic representations in the human brain. It may be this repurposing that allowed for the generation or mergence of hierarchical linguistic structure, and therefore, human language, from extant cognitive and neural systems. We conclude that models of thinking and reasoning and models of language processing must be integrated —not only for increased plausiblity, but in order to advance both fields towards a larger integrative model of human cognition
  • Drexler, H., Verbunt, A., & Wittenburg, P. (1996). Max Planck Electronic Information Desk. In B. den Brinker, J. Beek, A. Hollander, & R. Nieuwboer (Eds.), Zesde workshop computers in de psychologie: Programma en uitgebreide samenvattingen (pp. 64-66). Amsterdam: Vrije Universiteit Amsterdam, IFKB.
  • 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.
  • Drozdova, P., Van Hout, R., & Scharenborg, O. (2016). Processing and adaptation to ambiguous sounds during the course of perceptual learning. In Proceedings of Interspeech 2016: The 17th Annual Conference of the International Speech Communication Association (pp. 2811-2815). doi:10.21437/Interspeech.2016-814.

    Abstract

    Listeners use their lexical knowledge to interpret ambiguous sounds, and retune their phonetic categories to include this ambiguous sound. Although there is ample evidence for lexically-guided retuning, the adaptation process is not fully understood. Using a lexical decision task with an embedded auditory semantic priming task, the present study investigates whether words containing an ambiguous sound are processed in the same way as “natural” words and whether adaptation to the ambiguous sound tends to equalize the processing of “ambiguous” and natural words. Analyses of the yes/no responses and reaction times to natural and “ambiguous” words showed that words containing an ambiguous sound were accepted as words less often and were processed slower than the same words without ambiguity. The difference in acceptance disappeared after exposure to approximately 15 ambiguous items. Interestingly, lower acceptance rates and slower processing did not have an effect on the processing of semantic information of the following word. However, lower acceptance rates of ambiguous primes predict slower reaction times of these primes, suggesting an important role of stimulus-specific characteristics in triggering lexically-guided perceptual learning.
  • 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.
  • Eryilmaz, K., Little, H., & De Boer, B. (2016). Using HMMs To Attribute Structure To Artificial Languages. In S. G. Roberts, C. Cuskley, L. McCrohon, L. Barceló-Coblijn, O. Feher, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11). Retrieved from http://evolang.org/neworleans/papers/125.html.

    Abstract

    We investigated the use of Hidden Markov Models (HMMs) as a way of representing repertoires of continuous signals in order to infer their building blocks. We tested the idea on a dataset from an artificial language experiment. The study demonstrates using HMMs for this purpose is viable, but also that there is a lot of room for refinement such as explicit duration modeling, incorporation of autoregressive elements and relaxing the Markovian assumption, in order to accommodate specific details.
  • 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.
  • Filippi, P., Congdon, J. V., Hoang, J., Bowling, D. L., Reber, S., Pašukonis, A., Hoeschele, M., Ocklenburg, S., de Boer, B., Sturdy, C. B., Newen, A., & Güntürkün, O. (2016). Humans Recognize Vocal Expressions Of Emotional States Universally Across Species. In The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11). Retrieved from http://evolang.org/neworleans/papers/91.html.

    Abstract

    The perception of danger in the environment can induce physiological responses (such as a heightened state of arousal) in animals, which may cause measurable changes in the prosodic modulation of the voice (Briefer, 2012). The ability to interpret the prosodic features of animal calls as an indicator of emotional arousal may have provided the first hominins with an adaptive advantage, enabling, for instance, the recognition of a threat in the surroundings. This ability might have paved the ability to process meaningful prosodic modulations in the emerging linguistic utterances.
  • Filippi, P., Ocklenburg, S., Bowling, D. L., Heege, L., Newen, A., Güntürkün, O., & de Boer, B. (2016). Multimodal Processing Of Emotional Meanings: A Hypothesis On The Adaptive Value Of Prosody. In The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11). Retrieved from http://evolang.org/neworleans/papers/90.html.

    Abstract

    Humans combine multiple sources of information to comprehend meanings. These sources can be characterized as linguistic (i.e., lexical units and/or sentences) or paralinguistic (e.g. body posture, facial expression, voice intonation, pragmatic context). Emotion communication is a special case in which linguistic and paralinguistic dimensions can simultaneously denote the same, or multiple incongruous referential meanings. Think, for instance, about when someone says “I’m sad!”, but does so with happy intonation and a happy facial expression. Here, the communicative channels express very specific (although conflicting) emotional states as denotations. In such cases of intermodal incongruence, are we involuntarily biased to respond to information in one channel over the other? We hypothesize that humans are involuntary biased to respond to prosody over verbal content and facial expression, since the ability to communicate socially relevant information such as basic emotional states through prosodic modulation of the voice might have provided early hominins with an adaptive advantage that preceded the emergence of segmental speech (Darwin 1871; Mithen, 2005). To address this hypothesis, we examined the interaction between multiple communicative channels in recruiting attentional resources, within a Stroop interference task (i.e. a task in which different channels give conflicting information; Stroop, 1935). In experiment 1, we used synonyms of “happy” and “sad” spoken with happy and sad prosody. Participants were asked to identify the emotion expressed by the verbal content while ignoring prosody (Word task) or vice versa (Prosody task). Participants responded faster and more accurately in the Prosody task. Within the Word task, incongruent stimuli were responded to more slowly and less accurately than congruent stimuli. In experiment 2, we adopted synonyms of “happy” and “sad” spoken in happy and sad prosody, while a happy or sad face was displayed. Participants were asked to identify the emotion expressed by the verbal content while ignoring prosody and face (Word task), to identify the emotion expressed by prosody while ignoring verbal content and face (Prosody task), or to identify the emotion expressed by the face while ignoring prosody and verbal content (Face task). Participants responded faster in the Face task and less accurately when the two non-focused channels were expressing an emotion that was incongruent with the focused one, as compared with the condition where all the channels were congruent. In addition, in the Word task, accuracy was lower when prosody was incongruent to verbal content and face, as compared with the condition where all the channels were congruent. Our data suggest that prosody interferes with emotion word processing, eliciting automatic responses even when conflicting with both verbal content and facial expressions at the same time. In contrast, although processed significantly faster than prosody and verbal content, faces alone are not sufficient to interfere in emotion processing within a three-dimensional Stroop task. Our findings align with the hypothesis that the ability to communicate emotions through prosodic modulation of the voice – which seems to be dominant over verbal content - is evolutionary older than the emergence of segmental articulation (Mithen, 2005; Fitch, 2010). This hypothesis fits with quantitative data suggesting that prosody has a vital role in the perception of well-formed words (Johnson & Jusczyk, 2001), in the ability to map sounds to referential meanings (Filippi et al., 2014), and in syntactic disambiguation (Soderstrom et al., 2003). This research could complement studies on iconic communication within visual and auditory domains, providing new insights for models of language evolution. Further work aimed at how emotional cues from different modalities are simultaneously integrated will improve our understanding of how humans interpret multimodal emotional meanings in real life interactions.
  • Frost, R. L. A., Monaghan, P., & Christiansen, M. H. (2016). Using Statistics to Learn Words and Grammatical Categories: How High Frequency Words Assist Language Acquisition. In A. Papafragou, D. Mirman, & J. Trueswell (Eds.), Proceedings of the 38th Annual Meeting of the Cognitive Science Society (CogSci 2016) (pp. 81-86). Austin, Tx: Cognitive Science Society. Retrieved from https://mindmodeling.org/cogsci2016/papers/0027/index.html.

    Abstract

    Recent studies suggest that high-frequency words may benefit speech segmentation (Bortfeld, Morgan, Golinkoff, & Rathbun, 2005) and grammatical categorisation (Monaghan, Christiansen, & Chater, 2007). To date, these tasks have been examined separately, but not together. We familiarised adults with continuous speech comprising repetitions of target words, and compared learning to a language in which targets appeared alongside high-frequency marker words. Marker words reliably preceded targets, and distinguished them into two otherwise unidentifiable categories. Participants completed a 2AFC segmentation test, and a similarity judgement categorisation test. We tested transfer to a word-picture mapping task, where words from each category were used either consistently or inconsistently to label actions/objects. Participants segmented the speech successfully, but only demonstrated effective categorisation when speech contained high-frequency marker words. The advantage of marker words extended to the early stages of the transfer task. Findings indicate the same high-frequency words may assist speech segmentation and grammatical categorisation.
  • 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.
  • Gannon, E., He, J., Gao, X., & Chaparro, B. (2016). RSVP Reading on a Smart Watch. In Proceedings of the Human Factors and Ergonomics Society 2016 Annual Meeting (pp. 1130-1134).

    Abstract

    Reading with Rapid Serial Visual Presentation (RSVP) has shown promise for optimizing screen space and increasing reading speed without compromising comprehension. Given the wide use of small-screen devices, the present study compared RSVP and traditional reading on three types of reading comprehension, reading speed, and subjective measures on a smart watch. Results confirm previous studies that show faster reading speed with RSVP without detracting from comprehension. Subjective data indicate that Traditional is strongly preferred to RSVP as a primary reading method. Given the optimal use of screen space, increased speed and comparable comprehension, future studies should focus on making RSVP a more comfortable format.
  • Gerwien, J., & Flecken, M. (2016). First things first? Top-down influences on event apprehension. In A. Papafragou, D. Grodner, D. Mirman, & J. Trueswell (Eds.), Proceedings of the 38th Annual Meeting of the Cognitive Science Society (CogSci 2016) (pp. 2633-2638). Austin, TX: Cognitive Science Society.

    Abstract

    Not much is known about event apprehension, the earliest stage of information processing in elicited language production studies, using pictorial stimuli. A reason for our lack of knowledge on this process is that apprehension happens very rapidly (<350 ms after stimulus onset, Griffin & Bock 2000), making it difficult to measure the process directly. To broaden our understanding of apprehension, we analyzed landing positions and onset latencies of first fixations on visual stimuli (pictures of real-world events) given short stimulus presentation times, presupposing that the first fixation directly results from information processing during apprehension
  • 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.
  • Hendricks, I., Lefever, E., Croijmans, I., Majid, A., & Van den Bosch, A. (2016). Very quaffable and great fun: Applying NLP to wine reviews. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics: Vol 2 (pp. 306-312). Stroudsburg, PA: Association for Computational Linguistics.

    Abstract

    We automatically predict properties of
    wines on the basis of smell and flavor de-
    scriptions from experts’ wine reviews. We
    show wine experts are capable of describ-
    ing their smell and flavor experiences in
    wine reviews in a sufficiently consistent
    manner, such that we can use their descrip-
    tions to predict properties of a wine based
    solely on language. The experimental re-
    sults show promising F-scores when using
    lexical and semantic information to predict
    the color, grape variety, country of origin,
    and price of a wine. This demonstrates,
    contrary to popular opinion, that wine ex-
    perts’ reviews really are informative.
  • Hintz, F., & Scharenborg, O. (2016). Neighbourhood density influences word recognition in native and non-native speech recognition in noise. In H. Van den Heuvel, B. Cranen, & S. Mattys (Eds.), Proceedings of the Speech Processing in Realistic Environments (SPIRE) workshop (pp. 46-47). Groningen.
  • Hintz, F., & Scharenborg, O. (2016). The effect of background noise on the activation of phonological and semantic information during spoken-word recognition. In Proceedings of Interspeech 2016: The 17th Annual Conference of the International Speech Communication Association (pp. 2816-2820).

    Abstract

    During spoken-word recognition, listeners experience phonological competition between multiple word candidates, which increases, relative to optimal listening conditions, when speech is masked by noise. Moreover, listeners activate semantic word knowledge during the word’s unfolding. Here, we replicated the effect of background noise on phonological competition and investigated to which extent noise affects the activation of semantic information in phonological competitors. Participants’ eye movements were recorded when they listened to sentences containing a target word and looked at three types of displays. The displays either contained a picture of the target word, or a picture of a phonological onset competitor, or a picture of a word semantically related to the onset competitor, each along with three unrelated distractors. The analyses revealed that, in noise, fixations to the target and to the phonological onset competitor were delayed and smaller in magnitude compared to the clean listening condition, most likely reflecting enhanced phonological competition. No evidence for the activation of semantic information in the phonological competitors was observed in noise and, surprisingly, also not in the clear. We discuss the implications of the lack of an effect and differences between the present and earlier studies.
  • 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).
  • Irivine, E., & Roberts, S. G. (2016). Deictic tools can limit the emergence of referential symbol systems. In S. G. Roberts, C. Cuskley, L. McCrohon, L. Barceló-Coblijn, O. Feher, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11). Retrieved from http://evolang.org/neworleans/papers/99.html.

    Abstract

    Previous experiments and models show that the pressure to communicate can lead to the emergence of symbols in specific tasks. The experiment presented here suggests that the ability to use deictic gestures can reduce the pressure for symbols to emerge in co-operative tasks. In the 'gesture-only' condition, pairs built a structure together in 'Minecraft', and could only communicate using a small range of gestures. In the 'gesture-plus' condition, pairs could also use sound to develop a symbol system if they wished. All pairs were taught a pointing convention. None of the pairs we tested developed a symbol system, and performance was no different across the two conditions. We therefore suggest that deictic gestures, and non-referential means of organising activity sequences, are often sufficient for communication. This suggests that the emergence of linguistic symbols in early hominids may have been late and patchy with symbols only emerging in contexts where they could significantly improve task success or efficiency. Given the communicative power of pointing however, these contexts may be fewer than usually supposed. An approach for identifying these situations is outlined.
  • 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.
  • 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.
  • Janssen, R., Dediu, D., & Moisik, S. R. (2016). Simple agents are able to replicate speech sounds using 3d vocal tract model. In S. G. Roberts, C. Cuskley, L. McCrohon, L. Barceló-Coblijn, O. Feher, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11). Retrieved from http://evolang.org/neworleans/papers/97.html.

    Abstract

    Many factors have been proposed to explain why groups of people use different speech sounds in their language. These range from cultural, cognitive, environmental (e.g., Everett, et al., 2015) to anatomical (e.g., vocal tract (VT) morphology). How could such anatomical properties have led to the similarities and differences in speech sound distributions between human languages?

    It is known that hard palate profile variation can induce different articulatory strategies in speakers (e.g., Brunner et al., 2009). That is, different hard palate profiles might induce a kind of bias on speech sound production, easing some types of sounds while impeding others. With a population of speakers (with a proportion of individuals) that share certain anatomical properties, even subtle VT biases might become expressed at a population-level (through e.g., bias amplification, Kirby et al., 2007). However, before we look into population-level effects, we should first look at within-individual anatomical factors. For that, we have developed a computer-simulated analogue for a human speaker: an agent. Our agent is designed to replicate speech sounds using a production and cognition module in a computationally tractable manner.

    Previous agent models have often used more abstract (e.g., symbolic) signals. (e.g., Kirby et al., 2007). We have equipped our agent with a three-dimensional model of the VT (the production module, based on Birkholz, 2005) to which we made numerous adjustments. Specifically, we used a 4th-order Bezier curve that is able to capture hard palate variation on the mid-sagittal plane (XXX, 2015). Using an evolutionary algorithm, we were able to fit the model to human hard palate MRI tracings, yielding high accuracy fits and using as little as two parameters. Finally, we show that the samples map well-dispersed to the parameter-space, demonstrating that the model cannot generate unrealistic profiles. We can thus use this procedure to import palate measurements into our agent’s production module to investigate the effects on acoustics. We can also exaggerate/introduce novel biases.

    Our agent is able to control the VT model using the cognition module.

    Previous research has focused on detailed neurocomputation (e.g., Kröger et al., 2014) that highlights e.g., neurobiological principles or speech recognition performance. However, the brain is not the focus of our current study. Furthermore, present-day computing throughput likely does not allow for large-scale deployment of these architectures, as required by the population model we are developing. Thus, the question whether a very simple cognition module is able to replicate sounds in a computationally tractable manner, and even generalize over novel stimuli, is one worthy of attention in its own right.

    Our agent’s cognition module is based on running an evolutionary algorithm on a large population of feed-forward neural networks (NNs). As such, (anatomical) bias strength can be thought of as an attractor basin area within the parameter-space the agent has to explore. The NN we used consists of a triple-layered (fully-connected), directed graph. The input layer (three neurons) receives the formants frequencies of a target-sound. The output layer (12 neurons) projects to the articulators in the production module. A hidden layer (seven neurons) enables the network to deal with nonlinear dependencies. The Euclidean distance (first three formants) between target and replication is used as fitness measure. Results show that sound replication is indeed possible, with Euclidean distance quickly approaching a close-to-zero asymptote.

    Statistical analysis should reveal if the agent can also: a) Generalize: Can it replicate sounds not exposed to during learning? b) Replicate consistently: Do different, isolated agents always converge on the same sounds? c) Deal with consolidation: Can it still learn new sounds after an extended learning phase (‘infancy’) has been terminated? Finally, a comparison with more complex models will be used to demonstrate robustness.
  • Janssen, R., Winter, B., Dediu, D., Moisik, S. R., & Roberts, S. G. (2016). Nonlinear biases in articulation constrain the design space of language. In S. G. Roberts, C. Cuskley, L. McCrohon, L. Barceló-Coblijn, O. Feher, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11). Retrieved from http://evolang.org/neworleans/papers/86.html.

    Abstract

    In Iterated Learning (IL) experiments, a participant’s learned output serves as the next participant’s learning input (Kirby et al., 2014). IL can be used to model cultural transmission and has indicated that weak biases can be amplified through repeated cultural transmission (Kirby et al., 2007). So, for example, structural language properties can emerge over time because languages come to reflect the cognitive constraints in the individuals that learn and produce the language. Similarly, we propose that languages may also reflect certain anatomical biases. Do sound systems adapt to the affordances of the articulation space induced by the vocal tract?
    The human vocal tract has inherent nonlinearities which might derive from acoustics and aerodynamics (cf. quantal theory, see Stevens, 1989) or biomechanics (cf. Gick & Moisik, 2015). For instance, moving the tongue anteriorly along the hard palate to produce a fricative does not result in large changes in acoustics in most cases, but for a small range there is an abrupt change from a perceived palato-alveolar [ʃ] to alveolar [s] sound (Perkell, 2012). Nonlinearities such as these might bias all human speakers to converge on a very limited set of phonetic categories, and might even be a basis for combinatoriality or phonemic ‘universals’.
    While IL typically uses discrete symbols, Verhoef et al. (2014) have used slide whistles to produce a continuous signal. We conducted an IL experiment with human subjects who communicated using a digital slide whistle for which the degree of nonlinearity is controlled. A single parameter (α) changes the mapping from slide whistle position (the ‘articulator’) to the acoustics. With α=0, the position of the slide whistle maps Bark-linearly to the acoustics. As α approaches 1, the mapping gets more double-sigmoidal, creating three plateaus where large ranges of positions map to similar frequencies. In more abstract terms, α represents the strength of a nonlinear (anatomical) bias in the vocal tract.
    Six chains (138 participants) of dyads were tested, each chain with a different, fixed α. Participants had to communicate four meanings by producing a continuous signal using the slide-whistle in a ‘director-matcher’ game, alternating roles (cf. Garrod et al., 2007).
    Results show that for high αs, subjects quickly converged on the plateaus. This quick convergence is indicative of a strong bias, repelling subjects away from unstable regions already within-subject. Furthermore, high αs lead to the emergence of signals that oscillate between two (out of three) plateaus. Because the sigmoidal spaces are spatially constrained, participants increasingly used the sequential/temporal dimension. As a result of this, the average duration of signals with high α was ~100ms longer than with low α. These oscillations could be an expression of a basis for phonemic combinatoriality.
    We have shown that it is possible to manipulate the magnitude of an articulator-induced non-linear bias in a slide whistle IL framework. The results suggest that anatomical biases might indeed constrain the design space of language. In particular, the signaling systems in our study quickly converged (within-subject) on the use of stable regions. While these conclusions were drawn from experiments using slide whistles with a relatively strong bias, weaker biases could possibly be amplified over time by repeated cultural transmission, and likely lead to similar outcomes.
  • Jeske, J., Kember, H., & Cutler, A. (2016). Native and non-native English speakers' use of prosody to predict sentence endings. In Proceedings of the 16th Australasian International Conference on Speech Science and Technology (SST2016).
  • 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.
  • Kember, H., Choi, J., & Cutler, A. (2016). Processing advantages for focused words in Korean. In J. Barnes, A. Brugos, S. Shattuck-Hufnagel, & N. Veilleux (Eds.), Proceedings of Speech Prosody 2016 (pp. 702-705).

    Abstract

    In Korean, focus is expressed in accentual phrasing. To ascertain whether words focused in this manner enjoy a processing advantage analogous to that conferred by focus as expressed in, e.g, English and Dutch, we devised sentences with target words in one of four conditions: prosodic focus, syntactic focus, prosodic + syntactic focus, and no focus as a control. 32 native speakers of Korean listened to blocks of 10 sentences, then were presented visually with words and asked whether or not they had heard them. Overall, words with focus were recognised significantly faster and more accurately than unfocused words. In addition, words with syntactic focus or syntactic + prosodic focus were recognised faster than words with prosodic focus alone. As for other languages, Korean focus confers processing advantage on the words carrying it. While prosodic focus does provide an advantage, however, syntactic focus appears to provide the greater beneficial effect for recognition memory
  • 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. (1996). Human language technology can modernize writing and grammar instruction. In COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2 (pp. 1005-1006). Stroudsburg, PA: Association for Computational Linguistics.
  • 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., & Janssen, S. (1996). Omspellen: Reuze(n)karwei of peule(n)schil? In H. Croll, & J. Creutzberg (Eds.), Proceedings of the 5e Dag van het Document (pp. 143-146). Projectbureau Croll en Creutzberg.
  • 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. (Ed.). (1998). Kaleidoskop [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (112).
  • Klein, W. (Ed.). (1976). Psycholinguistik [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (23/24).
  • Klein, W., & Schlieben-Lange, B. (Eds.). (1996). Sprache und Subjektivität I [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (101).
  • Klein, W., & Schlieben-Lange, B. (Eds.). (1996). Sprache und Subjektivität II [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (102).
  • Klein, W. (Ed.). (1996). Zweitspracherwerb [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (104).
  • Klein, W. (Ed.). (1982). Zweitspracherwerb [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (45).
  • Kuijpers, C., Van Donselaar, W., & Cutler, A. (1996). Phonological variation: Epenthesis and deletion of schwa in Dutch. In H. T. Bunnell (Ed.), Proceedings of the Fourth International Conference on Spoken Language Processing: Vol. 1 (pp. 94-97). New York: Institute of Electrical and Electronics Engineers.

    Abstract

    Two types of phonological variation in Dutch, resulting from optional rules, are schwa epenthesis and schwa deletion. In a lexical decision experiment it was investigated whether the phonological variants were processed similarly to the standard forms. It was found that the two types of variation patterned differently. Words with schwa epenthesis were processed faster and more accurately than the standard forms, whereas words with schwa deletion led to less fast and less accurate responses. The results are discussed in relation to the role of consonant-vowel alternations in speech processing and the perceptual integrity of onset clusters.
  • 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).
  • Levshina, N., & Moran, S. (Eds.). (2021). Efficiency in human languages: Corpus evidence for universal principles [Special Issue]. Linguistics Vanguard, 7(s3).
  • Little, H., Eryılmaz, K., & De Boer, B. (2016). Differing signal-meaning dimensionalities facilitates the emergence of structure. In S. G. Roberts, C. Cuskley, L. McCrohon, L. Barceló-Coblijn, O. Feher, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11). Retrieved from http://evolang.org/neworleans/papers/25.html.

    Abstract

    Structure of language is not only caused by cognitive processes, but also by physical aspects of the signalling modality. We test the assumptions surrounding the role which the physical aspects of the signal space will have on the emergence of structure in speech. Here, we use a signal creation task to test whether a signal space and a meaning space having similar dimensionalities will generate an iconic system with signal-meaning mapping and whether, when the topologies differ, the emergence of non-iconic structure is facilitated. In our experiments, signals are created using infrared sensors which use hand position to create audio signals. We find that people take advantage of signal-meaning mappings where possible. Further, we use trajectory probabilities and measures of variance to show that when there is a dimensionality mismatch, more structural strategies are used.
  • Little, H., Eryılmaz, K., & De Boer, B. (2016). Emergence of signal structure: Effects of duration constraints. In S. G. Roberts, C. Cuskley, L. McCrohon, L. Barceló-Coblijn, O. Feher, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11). Retrieved from http://evolang.org/neworleans/papers/25.html.

    Abstract

    Recent work has investigated the emergence of structure in speech using experiments which use artificial continuous signals. Some experiments have had no limit on the duration which signals can have (e.g. Verhoef et al., 2014), and others have had time limitations (e.g. Verhoef et al., 2015). However, the effect of time constraints on the structure in signals has never been experimentally investigated.
  • Little, H., & de Boer, B. (2016). Did the pressure for discrimination trigger the emergence of combinatorial structure? In Proceedings of the 2nd Conference of the International Association for Cognitive Semiotics (pp. 109-110).
  • Little, H. (2016). Nahran Bhannamz: Language Evolution in an Online Zombie Apocalypse Game. In Createvolang: creativity and innovation in language evolution.
  • Lockwood, G., Hagoort, P., & Dingemanse, M. (2016). Synthesized Size-Sound Sound Symbolism. In A. Papafragou, D. Grodner, D. Mirman, & J. Trueswell (Eds.), Proceedings of the 38th Annual Meeting of the Cognitive Science Society (CogSci 2016) (pp. 1823-1828). Austin, TX: Cognitive Science Society.

    Abstract

    Studies of sound symbolism have shown that people can associate sound and meaning in consistent ways when presented with maximally contrastive stimulus pairs of nonwords such as bouba/kiki (rounded/sharp) or mil/mal (small/big). Recent work has shown the effect extends to antonymic words from natural languages and has proposed a role for shared cross-modal correspondences in biasing form-to-meaning associations. An important open question is how the associations work, and particularly what the role is of sound-symbolic matches versus mismatches. We report on a learning task designed to distinguish between three existing theories by using a spectrum of sound-symbolically matching, mismatching, and neutral (neither matching nor mismatching) stimuli. Synthesized stimuli allow us to control for prosody, and the inclusion of a neutral condition allows a direct test of competing accounts. We find evidence for a sound-symbolic match boost, but not for a mismatch difficulty compared to the neutral condition.
  • 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.
  • Macuch Silva, V., & Roberts, S. G. (2016). Language adapts to signal disruption in interaction. In S. G. Roberts, C. Cuskley, L. McCrohon, L. Barceló-Coblijn, O. Feher, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11). Retrieved from http://evolang.org/neworleans/papers/20.html.

    Abstract

    Linguistic traits are often seen as reflecting cognitive biases and constraints (e.g. Christiansen & Chater, 2008). However, language must also adapt to properties of the channel through which communication between individuals occurs. Perhaps the most basic aspect of any communication channel is noise. Communicative signals can be blocked, degraded or distorted by other sources in the environment. This poses a fundamental problem for communication. On average, channel disruption accompanies problems in conversation every 3 minutes (27% of cases of other-initiated repair, Dingemanse et al., 2015). Linguistic signals must adapt to this harsh environment. While modern language structures are robust to noise (e.g. Piantadosi et al., 2011), we investigate how noise might have shaped the early emergence of structure in language. The obvious adaptation to noise is redundancy. Signals which are maximally different from competitors are harder to render ambiguous by noise. Redundancy can be increased by adding differentiating segments to each signal (increasing the diversity of segments). However, this makes each signal more complex and harder to learn. Under this strategy, holistic languages may emerge. Another strategy is reduplication - repeating parts of the signal so that noise is less likely to disrupt all of the crucial information. This strategy does not increase the difficulty of learning the language - there is only one extra rule which applies to all signals. Therefore, under pressures for learnability, expressivity and redundancy, reduplicated signals are expected to emerge. However, reduplication is not a pervasive feature of words (though it does occur in limited domains like plurals or iconic meanings). We suggest that this is due to the pressure for redundancy being lifted by conversational infrastructure for repair. Receivers can request that senders repeat signals only after a problem occurs. That is, robustness is achieved by repeating the signal across conversational turns (when needed) instead of within single utterances. As a proof of concept, we ran two iterated learning chains with pairs of individuals in generations learning and using an artificial language (e.g. Kirby et al., 2015). The meaning space was a structured collection of unfamiliar images (3 shapes x 2 textures x 2 outline types). The initial language for each chain was the same written, unstructured, fully expressive language. Signals produced in each generation formed the training language for the next generation. Within each generation, pairs played an interactive communication game. The director was given a target meaning to describe, and typed a word for the matcher, who guessed the target meaning from a set. With a 50% probability, a contiguous section of 3-5 characters in the typed word was replaced by ‘noise’ characters (#). In one chain, the matcher could initiate repair by requesting that the director type and send another signal. Parallel generations across chains were matched for the number of signals sent (if repair was initiated for a meaning, then it was presented twice in the parallel generation where repair was not possible) and noise (a signal for a given meaning which was affected by noise in one generation was affected by the same amount of noise in the parallel generation). For the final set of signals produced in each generation we measured the signal redundancy (the zip compressibility of the signals), the character diversity (entropy of the characters of the signals) and systematic structure (z-score of the correlation between signal edit distance and meaning hamming distance). In the condition without repair, redundancy increased with each generation (r=0.97, p=0.01), and the character diversity decreased (r=-0.99,p=0.001) which is consistent with reduplication, as shown below (part of the initial and the final language): Linear regressions revealed that generations with repair had higher overall systematic structure (main effect of condition, t = 2.5, p < 0.05), increasing character diversity (interaction between condition and generation, t = 3.9, p = 0.01) and redundancy increased at a slower rate (interaction between condition and generation, t = -2.5, p < 0.05). That is, the ability to repair counteracts the pressure from noise, and facilitates the emergence of compositional structure. Therefore, just as systems to repair damage to DNA replication are vital for the evolution of biological species (O’Brien, 2006), conversational repair may regulate replication of linguistic forms in the cultural evolution of language. Future studies should further investigate how evolving linguistic structure is shaped by interaction pressures, drawing on experimental methods and naturalistic studies of emerging languages, both spoken (e.g Botha, 2006; Roberge, 2008) and signed (e.g Senghas, Kita, & Ozyurek, 2004; Sandler et al., 2005).
  • 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.
  • 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.
  • Meyer, A. S., & Huettig, F. (Eds.). (2016). Speaking and Listening: Relationships Between Language Production and Comprehension [Special Issue]. Journal of Memory and Language, 89.

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