Displaying 1 - 25 of 25
  • Ergin, R., Raviv, L., Senghas, A., Padden, C., & Sandler, W. (2020). Community structure affects convergence on uniform word orders: Evidence from emerging sign languages. In A. Ravignani, C. Barbieri, M. Flaherty, Y. Jadoul, E. Lattenkamp, H. Little, M. Martins, K. Mudd, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 13th International Conference (Evolang13) (pp. 84-86). Nijmegen: The Evolution of Language Conferences.
  • Hashemzadeh, M., Kaufeld, G., White, M., Martin, A. E., & Fyshe, A. (2020). From language to language-ish: How brain-like is an LSTM representation of nonsensical language stimuli? In T. Cohn, Y. He, & Y. Liu (Eds.), Findings of the Association for Computational Linguistics: EMNLP 2020 (pp. 645-655). Association for Computational Linguistics.

    Abstract

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

    Abstract

    A central question in the psycholinguistic study of multilingualism is how syntax is shared across languages. We implement a model to investigate whether error-based implicit learning can provide an account of cross-language structural priming. The model is based on the Dual-path model of
    sentence-production (Chang, 2002). We implement our model using the Bilingual version of Dual-path (Tsoukala, Frank, & Broersma, 2017). We answer two main questions: (1) Can structural priming of active and passive constructions occur between English and Spanish in a bilingual version of the Dual-
    path model? (2) Does cross-language priming differ quantitatively from within-language priming in this model? Our results show that cross-language priming does occur in the model. This finding adds to the viability of implicit learning as an account of structural priming in general and cross-language
    structural priming specifically. Furthermore, we find that the within-language priming effect is somewhat stronger than the cross-language effect. In the context of mixed results from
    behavioral studies, we interpret the latter finding as an indication that the difference between cross-language and within-
    language priming is small and difficult to detect statistically.
  • Lattenkamp, E. Z., Linnenschmidt, M., Mardus, E., Vernes, S. C., Wiegrebe, L., & Schutte, M. (2020). Impact of auditory feedback on bat vocal development. In A. Ravignani, C. Barbieri, M. Flaherty, Y. Jadoul, E. Lattenkamp, H. Little, M. Martins, K. Mudd, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 13th International Conference (Evolang13) (pp. 249-251). Nijmegen: The Evolution of Language Conferences.
  • Lei, L., Raviv, L., & Alday, P. M. (2020). Using spatial visualizations and real-world social networks to understand language evolution and change. In A. Ravignani, C. Barbieri, M. Flaherty, Y. Jadoul, E. Lattenkamp, H. Little, M. Martins, K. Mudd, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 13th International Conference (Evolang13) (pp. 252-254). Nijmegen: The Evolution of Language Conferences.
  • Mengede, J., Devanna, P., Hörpel, S. G., Firzla, U., & Vernes, S. C. (2020). Studying the genetic bases of vocal learning in bats. In A. Ravignani, C. Barbieri, M. Flaherty, Y. Jadoul, E. Lattenkamp, H. Little, M. Martins, K. Mudd, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 13th International Conference (Evolang13) (pp. 280-282). Nijmegen: The Evolution of Language Conferences.
  • Mudd, K., Lutzenberger, H., De Vos, C., Fikkert, P., Crasborn, O., & De Boer, B. (2020). How does social structure shape language variation? A case study of the Kata Kolok lexicon. In A. Ravignani, C. Barbieri, M. Flaherty, Y. Jadoul, E. Lattenkamp, H. Little, M. Martins, K. Mudd, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 13th International Conference (Evolang13) (pp. 302-304). Nijmegen: The Evolution of Language Conferences.
  • Rasenberg, M., Dingemanse, M., & Ozyurek, A. (2020). Lexical and gestural alignment in interaction and the emergence of novel shared symbols. In A. Ravignani, C. Barbieri, M. Flaherty, Y. Jadoul, E. Lattenkamp, H. Little, M. Martins, K. Mudd, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 13th International Conference (Evolang13) (pp. 356-358). Nijmegen: The Evolution of Language Conferences.
  • Raviv, L., Meyer, A. S., & Lev-Ari, S. (2020). Network structure and the cultural evolution of linguistic structure: A group communication experiment. In A. Ravignani, C. Barbieri, M. Flaherty, Y. Jadoul, E. Lattenkamp, H. Little, M. Martins, K. Mudd, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 13th International Conference (Evolang13) (pp. 359-361). Nijmegen: The Evolution of Language Conferences.
  • Ter Bekke, M., Drijvers, L., & Holler, J. (2020). The predictive potential of hand gestures during conversation: An investigation of the timing of gestures in relation to speech. In Proceedings of the 7th GESPIN - Gesture and Speech in Interaction Conference. Stockholm: KTH Royal Institute of Technology.

    Abstract

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

    Abstract

    Multilingual speakers are able to switch from
    one language to the other (“code-switch”) be-
    tween or within sentences. Because the under-
    lying cognitive mechanisms are not well un-
    derstood, in this study we use computational
    cognitive modeling to shed light on the pro-
    cess of code-switching. We employed the
    Bilingual Dual-path model, a Recurrent Neu-
    ral Network of bilingual sentence production
    (Tsoukala et al., 2017) and simulated sentence
    production in simultaneous Spanish-English
    bilinguals. Our first goal was to investigate
    whether the model would code-switch with-
    out being exposed to code-switched training
    input. The model indeed produced code-
    switches even without any exposure to such
    input and the patterns of code-switches are
    in line with earlier linguistic work (Poplack,
    1980). The second goal of this study was to
    investigate an auxiliary phrase asymmetry that
    exists in Spanish-English code-switched pro-
    duction. Using this cognitive model, we ex-
    amined a possible cause for this asymmetry.
    To our knowledge, this is the first computa-
    tional cognitive model that aims to simulate
    code-switched sentence production.
  • Yang, J., Van den Bosch, A., & Frank, S. L. (2020). Less is Better: A cognitively inspired unsupervised model for language segmentation. In M. Zock, E. Chersoni, A. Lenci, & E. Santus (Eds.), Proceedings of the Workshop on the Cognitive Aspects of the Lexicon ( 28th International Conference on Computational Linguistics) (pp. 33-45). Stroudsburg: Association for Computational Linguistics.

    Abstract

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

    Additional information

    full text via ACL website
  • Bergmann, C., Paulus, M., & Fikkert, J. (2010). A closer look at pronoun comprehension: Comparing different methods. In J. Costa, A. Castro, M. Lobo, & F. Pratas (Eds.), Language Acquisition and Development: Proceedings of GALA 2009 (pp. 53-61). Newcastle upon Tyne: Cambridge Scholars Publishing.

    Abstract

    1. Introduction External input is necessary to acquire language. Consequently, the comprehension of various constituents of language, such as lexical items or syntactic and semantic structures should emerge at the same time as or even precede their production. However, in the case of pronouns this general assumption does not seem to hold. On the contrary, while children at the age of four use pronouns and reflexives appropriately during production (de Villiers, et al. 2006), a number of comprehension studies across different languages found chance performance in pronoun trials up to the age of seven, which co-occurs with a high level of accuracy in reflexive trials (for an overview see e.g. Conroy, et al. 2009; Elbourne 2005).
  • Bergmann, C., Gubian, M., & Boves, L. (2010). Modelling the effect of speaker familiarity and noise on infant word recognition. In Proceedings of the 11th Annual Conference of the International Speech Communication Association [Interspeech 2010] (pp. 2910-2913). ISCA.

    Abstract

    In the present paper we show that a general-purpose word learning model can simulate several important findings from recent experiments in language acquisition. Both the addition of background noise and varying the speaker have been found to influence infants’ performance during word recognition experiments. We were able to replicate this behaviour in our artificial word learning agent. We use the results to discuss both advantages and limitations of computational models of language acquisition.
  • Dolscheid, S., Shayan, S., Ozturk, O., Majid, A., & Casasanto, D. (2010). Language shapes mental representations of musical pitch: Implications for metaphorical language processing [Abstract]. In Proceedings of the 16th Annual Conference on Architectures and Mechanisms for Language Processing [AMLaP 2010] (pp. 137). York: University of York.

    Abstract

    Speakers often use spatial metaphors to talk about musical pitch (e.g., a low note, a high soprano). Previous experiments suggest that English speakers also think about pitches as high or low in space, even when theyʼre not using language or musical notation (Casasanto, 2010). Do metaphors in language merely reflect pre-existing associations between space and pitch, or might language also shape these non-linguistic metaphorical mappings? To investigate the role of language in pitch tepresentation, we conducted a pair of non-linguistic spacepitch interference experiments in speakers of two languages that use different spatial metaphors. Dutch speakers usually describe pitches as ʻhighʼ (hoog) and ʻlowʼ (laag). Farsi speakers, however, often describe high-frequency pitches as ʻthinʼ (naazok) and low-frequency pitches as ʻthickʼ (koloft). Do Dutch and Farsi speakers mentally represent pitch differently? To find out, we asked participants to reproduce musical pitches that they heard in the presence of irrelevant spatial information (i.e., lines that varied either in height or in thickness). For the Height Interference experiment, horizontal lines bisected a vertical reference line at one of nine different locations. For the Thickness Interference experiment, a vertical line appeared in the middle of the screen in one of nine thicknesses. In each experiment, the nine different lines were crossed with nine different pitches ranging from C4 to G#4 in semitone increments, to produce 81 distinct trials. If Dutch and Farsi speakers mentally represent pitch the way they talk about it, using different kinds of spatial representations, they should show contrasting patterns of cross-dimensional interference: Dutch speakersʼ pitch estimates should be more strongly affected by irrelevant height information, and Farsi speakersʼ by irrelevant thickness information. As predicted, Dutch speakersʼ pitch estimates were significantly modulated by spatial height but not by thickness. Conversely, Farsi speakersʼ pitch estimates were modulated by spatial thickness but not by height (2x2 ANOVA on normalized slopes of the effect of space on pitch: F(1,71)=17,15 p<.001). To determine whether language plays a causal role in shaping pitch representations, we conducted a training experiment. Native Dutch speakers learned to use Farsi-like metaphors, describing pitch relationships in terms of thickness (e.g., a cello sounds ʻthickerʼ than a flute). After training, Dutch speakers showed a significant effect of Thickness interference in the non-linguistic pitch reproduction task, similar to native Farsi speakers: on average, pitches accompanied by thicker lines were reproduced as lower in pitch (effect of thickness on pitch: r=-.22, p=.002). By conducting psychophysical tasks, we tested the ʻWhorfianʼ question without using words. Yet, results also inform theories of metaphorical language processing. According to psycholinguistic theories (e.g., Bowdle & Gentner, 2005), highly conventional metaphors are processed without any active mapping from the source to the target domain (e.g., from space to pitch). Our data, however, suggest that when people use verbal metaphors they activate a corresponding non-linguistic mapping from either height or thickness to pitch, strengthening this association at the expense of competing associations. As a result, people who use different metaphors in their native languages form correspondingly different representations of musical pitch. Casasanto, D. (2010). Space for Thinking. In Language, Cognition and Space: State of the art and new directions. V. Evans & P. Chilton (Eds.), 453-478, London: Equinox Publishing. Bowdle, B. & Gentner, D. (2005). The career of metaphor. Psychological Review, 112, 193-216.
  • Gubian, M., Bergmann, C., & Boves, L. (2010). Investigating word learning processes in an artificial agent. In Proceedings of the IXth IEEE International Conference on Development and Learning (ICDL). Ann Arbor, MI, 18-21 Aug. 2010 (pp. 178 -184). IEEE.

    Abstract

    Researchers in human language processing and acquisition are making an increasing use of computational models. Computer simulations provide a valuable platform to reproduce hypothesised learning mechanisms that are otherwise very difficult, if not impossible, to verify on human subjects. However, computational models come with problems and risks. It is difficult to (automatically) extract essential information about the developing internal representations from a set of simulation runs, and often researchers limit themselves to analysing learning curves based on empirical recognition accuracy through time. The associated risk is to erroneously deem a specific learning behaviour as generalisable to human learners, while it could also be a mere consequence (artifact) of the implementation of the artificial learner or of the input coding scheme. In this paper a set of simulation runs taken from the ACORNS project is investigated. First a look `inside the box' of the learner is provided by employing novel quantitative methods for analysing changing structures in large data sets. Then, the obtained findings are discussed in the perspective of their ecological validity in the field of child language acquisition.
  • Kung, C., Chwilla, D. J., Gussenhoven, C., Bögels, S., & Schriefers, H. (2010). What did you say just now, bitterness or wife? An ERP study on the interaction between tone, intonation and context in Cantonese Chinese. In Proceedings of Speech Prosody 2010 (pp. 1-4).

    Abstract

    Previous studies on Cantonese Chinese showed that rising
    question intonation contours on low-toned words lead to
    frequent misperceptions of the tones. Here we explored the
    processing consequences of this interaction between tone and
    intonation by comparing the processing and identification of
    monosyllabic critical words at the end of questions and
    statements, using a tone identification task, and ERPs as an
    online measure of speech comprehension. Experiment 1
    yielded higher error rates for the identification of low tones at
    the end of questions and a larger N400-P600 pattern, reflecting
    processing difficulty and reanalysis, compared to other
    conditions. In Experiment 2, we investigated the effect of
    immediate lexical context on the tone by intonation interaction.
    Increasing contextual constraints led to a reduction in errors
    and the disappearance of the P600 effect. These results
    indicate that there is an immediate interaction between tone,
    intonation, and context in online speech comprehension. The
    difference in performance and activation patterns between the
    two experiments highlights the significance of context in
    understanding a tone language, like Cantonese-Chinese.
  • Versteegh, M., Ten Bosch, L., & Boves, L. (2010). Active word learning under uncertain input conditions. In Proceedings of the 11th Annual Conference of the International Speech Communication Association (Interspeech 2010), Makuhari, Japan (pp. 2930-2933). ISCA.

    Abstract

    This paper presents an analysis of phoneme durations of emotional speech in two languages: Dutch and Korean. The analyzed corpus of emotional speech has been specifically developed for the purpose of cross-linguistic comparison, and is more balanced than any similar corpus available so far: a) it contains expressions by both Dutch and Korean actors and is based on judgments by both Dutch and Korean listeners; b) the same elicitation technique and recording procedure were used for recordings of both languages; and c) the phonetics of the carrier phrase were constructed to be permissible in both languages. The carefully controlled phonetic content of the carrier phrase allows for analysis of the role of specific phonetic features, such as phoneme duration, in emotional expression in Dutch and Korean. In this study the mutual effect of language and emotion on phoneme duration is presented.
  • Versteegh, M., Ten Bosch, L., & Boves, L. (2010). Dealing with uncertain input in word learning. In Proceedings of the IXth IEEE International Conference on Development and Learning (ICDL). Ann Arbor, MI, 18-21 Aug. 2010 (pp. 46-51). IEEE.

    Abstract

    In this paper we investigate a computational model of word learning, that is embedded in a cognitively and ecologically plausible framework. Multi-modal stimuli from four different speakers form a varied source of experience. The model incorporates active learning, attention to a communicative setting and clarity of the visual scene. The model's ability to learn associations between speech utterances and visual concepts is evaluated during training to investigate the influence of active learning under conditions of uncertain input. The results show the importance of shared attention in word learning and the model's robustness against noise.
  • Versteegh, M., Sangati, F., & Zuidema, W. (2010). Simulations of socio-linguistic change: Implications for unidirectionality. In A. Smith, M. Schoustra, B. Boer, & K. Smith (Eds.), Proceedings of the 8th International conference on the Evolution of Language (EVOLANG 8) (pp. 511-512). World Scientific Publishing.
  • Weber, A., & Poellmann, K. (2010). Identifying foreign speakers with an unfamiliar accent or in an unfamiliar language. In New Sounds 2010: Sixth International Symposium on the Acquisition of Second Language Speech (pp. 536-541). Poznan, Poland: Adam Mickiewicz University.
  • Witteman, M. J., Weber, A., & McQueen, J. M. (2010). Rapid and long-lasting adaptation to foreign-accented speech [Abstract]. Journal of the Acoustical Society of America, 128, 2486.

    Abstract

    In foreign-accented speech, listeners have to handle noticeable deviations from the standard pronunciation of a target language. Three cross-modal priming experiments investigated how short- and long-term experiences with a foreign accent influence word recognition by native listeners. In experiment 1, German-accented words were presented to Dutch listeners who had either extensive or limited prior experience with German-accented Dutch. Accented words either contained a diphthong substitution that deviated acoustically quite largely from the canonical form (huis [hys], "house", pronounced as [hoys]), or that deviated acoustically to a lesser extent (lijst [lst], "list", pronounced as [lst]). The mispronunciations never created lexical ambiguity in Dutch. While long-term experience facilitated word recognition for both types of substitutions, limited experience facilitated recognition only of words with acoustically smaller deviations. In experiment 2, Dutch listeners with limited experience listened to the German speaker for 4 min before participating in the cross-modal priming experiment. The results showed that speaker-specific learning effects for acoustically large deviations can be obtained already after a brief exposure, as long as the exposure contains evidence of the deviations. Experiment 3 investigates whether these short-term adaptation effects for foreign-accented speech are speaker-independent.

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