Publications

Displaying 1 - 100 of 177
  • 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.
  • Anastasopoulos, A., Lekakou, M., Quer, J., Zimianiti, E., DeBenedetto, J., & Chiang, D. (2018). Part-of-speech tagging on an endangered language: a parallel Griko-Italian Resource. In Proceedings of the 27th International Conference on Computational Linguistics (COLING 2018) (pp. 2529-2539).

    Abstract

    Most work on part-of-speech (POS) tagging is focused on high resource languages, or examines low-resource and active learning settings through simulated studies. We evaluate POS tagging techniques on an actual endangered language, Griko. We present a resource that contains 114 narratives in Griko, along with sentence-level translations in Italian, and provides gold annotations for the test set. Based on a previously collected small corpus, we investigate several traditional methods, as well as methods that take advantage of monolingual data or project cross-lingual POS tags. We show that the combination of a semi-supervised method with cross-lingual transfer is more appropriate for this extremely challenging setting, with the best tagger achieving an accuracy of 72.9%. With an applied active learning scheme, which we use to collect sentence-level annotations over the test set, we achieve improvements of more than 21 percentage points
  • 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
  • Bauer, B. L. M. (2016). The development of the comparative in Latin texts. In J. N. Adams, & N. Vincent (Eds.), Early and late Latin. Continuity or change? (pp. 313-339). Cambridge: Cambridge University Press.
  • 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
  • Blythe, J. (2018). Genesis of the trinity: The convergent evolution of trirelational kinterms. In P. McConvell, & P. Kelly (Eds.), Skin, kin and clan: The dynamics of social categories in Indigenous Australia (pp. 431-471). Canberra: ANU EPress.
  • 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
  • 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.
  • Brehm, L., & Goldrick, M. (2018). Connectionist principles in theories of speech production. In S.-A. Rueschemeyer, & M. G. Gaskell (Eds.), The Oxford Handbook of Psycholinguistics (2nd ed., pp. 372-397). Oxford: Oxford University Press.

    Abstract

    This chapter focuses on connectionist modeling in language production, highlighting how
    core principles of connectionism provide coverage for empirical observations about
    representation and selection at the phonological, lexical, and sentence levels. The first
    section focuses on the connectionist principles of localist representations and spreading
    activation. It discusses how these two principles have motivated classic models of speech
    production and shows how they cover results of the picture-word interference paradigm,
    the mixed error effect, and aphasic naming errors. The second section focuses on how
    newer connectionist models incorporate the principles of learning and distributed
    representations through discussion of syntactic priming, cumulative semantic
    interference, sequencing errors, phonological blends, and code-switching
  • Brown, P., & Levinson, S. C. (2018). Tzeltal: The demonstrative system. In S. C. Levinson, S. Cutfield, M. Dunn, N. J. Enfield, & S. Meira (Eds.), Demonstratives in cross-linguistic perspective (pp. 150-177). Cambridge: Cambridge University Press.
  • 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).
  • Burenhult, N., & Kruspe, N. (2016). The language of eating and drinking: A window on Orang Asli meaning-making. In K. Endicott (Ed.), Malaysia’s original people: Past, present and future of the Orang Asli (pp. 175-199). Singapore: National University of Singapore Press.
  • 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.
  • Clark, E. V., & Casillas, M. (2016). First language acquisition. In K. Allen (Ed.), The Routledge Handbook of Linguistics (pp. 311-328). New York: Routledge.
  • 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
  • Ip, M. H. K., & Cutler, A. (2018). Asymmetric efficiency of juncture perception in L1 and L2. In K. Klessa, J. Bachan, A. Wagner, M. Karpiński, & D. Śledziński (Eds.), Proceedings of Speech Prosody 2018 (pp. 289-296). Baixas, France: ISCA. doi:10.21437/SpeechProsody.2018-59.

    Abstract

    In two experiments, Mandarin listeners resolved potential syntactic ambiguities in spoken utterances in (a) their native language (L1) and (b) English which they had learned as a second language (L2). A new disambiguation task was used, requiring speeded responses to select the correct meaning for structurally ambiguous sentences. Importantly, the ambiguities used in the study are identical in Mandarin and in English, and production data show that prosodic disambiguation of this type of ambiguity is also realised very similarly in the two languages. The perceptual results here showed however that listeners’ response patterns differed for L1 and L2, although there was a significant increase in similarity between the two response patterns with increasing exposure to the L2. Thus identical ambiguity and comparable disambiguation patterns in L1 and L2 do not lead to immediate application of the appropriate L1 listening strategy to L2; instead, it appears that such a strategy may have to be learned anew for the L2.
  • Ip, M., & 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., Burchfield, L. A., & Antoniou, M. (2018). Factors affecting talker adaptation in a second language. In J. Epps, J. Wolfe, J. Smith, & C. Jones (Eds.), Proceedings of the 17th Australasian International Conference on Speech Science and Technology (pp. 33-36).

    Abstract

    Listeners adapt rapidly to previously unheard talkers by
    adjusting phoneme categories using lexical knowledge, in a
    process termed lexically-guided perceptual learning. Although
    this is firmly established for listening in the native language
    (L1), perceptual flexibility in second languages (L2) is as yet
    less well understood. We report two experiments examining L1
    and L2 perceptual learning, the first in Mandarin-English late
    bilinguals, the second in Australian learners of Mandarin. Both
    studies showed stronger learning in L1; in L2, however,
    learning appeared for the English-L1 group but not for the
    Mandarin-L1 group. Phonological mapping differences from
    the L1 to the L2 are suggested as the reason for this result.
  • Cutler, A., & Farrell, J. (2018). Listening in first and second language. In J. I. Liontas (Ed.), The TESOL encyclopedia of language teaching. New York: Wiley. doi:10.1002/9781118784235.eelt0583.

    Abstract

    Listeners' recognition of spoken language involves complex decoding processes: The continuous speech stream must be segmented into its component words, and words must be recognized despite great variability in their pronunciation (due to talker differences, or to influence of phonetic context, or to speech register) and despite competition from many spuriously present forms supported by the speech signal. L1 listeners deal more readily with all levels of this complexity than L2 listeners. Fortunately, the decoding processes necessary for competent L2 listening can be taught in the classroom. Evidence-based methodologies targeted at the development of efficient speech decoding include teaching of minimal pairs, of phonotactic constraints, and of reduction processes, as well as the use of dictation and L2 video captions.
  • 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.
  • Dingemanse, M., Blythe, J., & Dirksmeyer, T. (2018). Formats for other-initiation of repair across languages: An exercise in pragmatic typology. In I. Nikolaeva (Ed.), Linguistic Typology: Critical Concepts in Linguistics. Vol. 4 (pp. 322-357). London: Routledge.

    Abstract

    In conversation, people regularly deal with problems of speaking, hearing, and understanding. We report on a cross-linguistic investigation of the conversational structure of other-initiated repair (also known as collaborative repair, feedback, requests for clarification, or grounding sequences). We take stock of formats for initiating repair across languages (comparable to English huh?, who?, y’mean X?, etc.) and find that different languages make available a wide but remarkably similar range of linguistic resources for this function. We exploit the patterned variation as evidence for several underlying concerns addressed by repair initiation: characterising trouble, managing responsibility, and handling knowledge. The concerns do not always point in the same direction and thus provide participants in interaction with alternative principles for selecting one format over possible others. By comparing conversational structures across languages, this paper contributes to pragmatic typology: the typology of systems of language use and the principles that shape them.
  • 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
  • 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.
  • Eisner, F., & McQueen, J. M. (2018). Speech perception. In S. Thompson-Schill (Ed.), Stevens’ handbook of experimental psychology and cognitive neuroscience (4th ed.). Volume 3: Language & thought (pp. 1-46). Hoboken: Wiley. doi:10.1002/9781119170174.epcn301.

    Abstract

    This chapter reviews the computational processes that are responsible for recognizing word forms in the speech stream. We outline the different stages in a processing hierarchy from the extraction of general acoustic features, through speech‐specific prelexical processes, to the retrieval and selection of lexical representations. We argue that two recurring properties of the system as a whole are abstraction and adaptability. We also present evidence for parallel processing of information on different timescales, more specifically that segmental material in the speech stream (its consonants and vowels) is processed in parallel with suprasegmental material (the prosodic structures of spoken words). We consider evidence from both psycholinguistics and neurobiology wherever possible, and discuss how the two fields are beginning to address common computational problems. The challenge for future research in speech perception will be to build an account that links these computational problems, through functional mechanisms that address them, to neurobiological implementation.
  • 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.
  • Ernestus, M. (2016). L'utilisation des corpus oraux pour la recherche en (psycho)linguistique. In M. Kilani-Schoch, C. Surcouf, & A. Xanthos (Eds.), Nouvelles technologies et standards méthodologiques en linguistique (pp. 65-93). Lausanne: Université de Lausanne.
  • Ernestus, M., & Smith, R. (2018). Qualitative and quantitative aspects of phonetic variation in Dutch eigenlijk. In F. Cangemi, M. Clayards, O. Niebuhr, B. Schuppler, & M. Zellers (Eds.), Rethinking reduction: Interdisciplinary perspectives on conditions, mechanisms, and domains for phonetic variation (pp. 129-163). Berlin/Boston: De Gruyter Mouton.
  • 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.
  • 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.
  • Fisher, S. E. (2016). A molecular genetic perspective on speech and language. In G. Hickok, & S. Small (Eds.), Neurobiology of Language (pp. 13-24). Amsterdam: Elsevier. doi:10.1016/B978-0-12-407794-2.00002-X.

    Abstract

    The rise of genomic technologies has yielded exciting new routes for studying the biological foundations of language. Researchers have begun to identify genes implicated in neurodevelopmental disorders that disrupt speech and language skills. This chapter illustrates how such work can provide powerful entry points into the critical neural pathways using FOXP2 as an example. Rare mutations of this gene cause problems with learning to sequence mouth movements during speech, accompanied by wide-ranging impairments in language production and comprehension. FOXP2 encodes a regulatory protein, a hub in a network of other genes, several of which have also been associated with language-related impairments. Versions of FOXP2 are found in similar form in many vertebrate species; indeed, studies of animals and birds suggest conserved roles in the development and plasticity of certain sets of neural circuits. Thus, the contributions of this gene to human speech and language involve modifications of evolutionarily ancient functions.
  • Flecken, M., & Von Stutterheim, C. (2018). Sprache und Kognition: Sprachvergleichende und lernersprachliche Untersuchungen zur Ereigniskonzeptualisierung. In S. Schimke, & H. Hopp (Eds.), Sprachverarbeitung im Zweitspracherwerb (pp. 325-356). Berlin: De Gruyter. doi:10.1515/9783110456356-014.
  • Floyd, S. (2018). Egophoricity and argument structure in Cha'palaa. In S. Floyd, E. Norcliffe, & L. San Roque (Eds.), Egophoricity (pp. 269-304). Amsterdam: Benjamins.

    Abstract

    The Cha’palaa language of Ecuador (Barbacoan) features verbal morphology for marking knowledge-based categories that, in usage, show a variant of the cross-linguistically recurrent pattern of ‘egophoric distribution': specific forms associate with speakers in contrast to others in statements and with addressees in contrast to others in questions. These are not person markers, but rather are used by speakers to portray their involvement in states of affairs as active, agentive participants (ego) versus other types of involvement (non-ego). They interact with person and argument structure, but through pragmatic ‘person sensitivities’ rather than through grammatical agreement. Not only does this pattern appear in verbal morphology, it also can be observed in alternations of predicate construction types and case alignment, helping to show how egophoric marking is a pervasive element of Cha'palaa's linguistic system. This chapter gives a first account of egophoricity in Cha’palaa, beginning with a discussion of person sensitivity, egophoric distribution, and issues of flexibility of marking with respect to degree of volition or control. It then focuses on a set of intransitive experiencer (or ‘endopathic') predicates that refer to internal states which mark egophoric values for the undergoer role, not the actor role, showing ‘quirky’ accusative marking instead of nominative case. It concludes with a summary of how egophoricity in Cha'palaa interacts with issues of argument structure in comparison to a language with person agreement, here represented by examples from Cha’palaa’s neighbor Ecuadorian Highland Quechua.
  • Floyd, S. (2016). Insubordination in Interaction: The Cha’palaa counter-assertive. In N. Evans, & H. Wananabe (Eds.), Dynamics of Insubordination (pp. 341-366). Amsterdam: John Benjamins.

    Abstract

    In the Cha’palaa language of Ecuador the main-clause use of the otherwise non-finite morpheme -ba can be accounted for by a specific interactive practice: the ‘counter-assertion’ of statement or implicature of a previous conversational turn. Attention to the ways in which different constructions are deployed in such recurrent conversational contexts reveals a plausible account for how this type of dependent clause has come to be one of the options for finite clauses. After giving some background on Cha’palaa and placing ba clauses within a larger ecology of insubordination constructions in the language, this chapter uses examples from a video corpus of informal conversation to illustrate how interactive data provides answers that may otherwise be elusive for understanding how the different grammatical options for Cha’palaa finite verb constructions have been structured by insubordination
  • Floyd, S., & Norcliffe, E. (2016). Switch reference systems in the Barbacoan languages and their neighbors. In R. Van Gijn, & J. Hammond (Eds.), Switch Reference 2.0 (pp. 207-230). Amsterdam: Benjamins.

    Abstract

    This chapter surveys the available data on Barbacoan languages and their neighbors to explore a case study of switch reference within a single language family and in a situation of areal contact. To the extent possible given the available data, we weigh accounts appealing to common inheritance and areal convergence to ask what combination of factors led to the current state of these languages. We discuss the areal distribution of switch reference systems in the northwest Andean region, the different types of systems and degrees of complexity observed, and scenarios of contact and convergence, particularly in the case of Barbacoan and Ecuadorian Quechua. We then covers each of the Barbacoan languages’ systems (with the exception of Totoró, represented by its close relative Guambiano), identifying limited formal cognates, primarily between closely-related Tsafiki and Cha’palaa, as well as broader functional similarities, particularly in terms of interactions with topic/focus markers. n accounts for the current state of affairs with a complex scenario of areal prevalence of switch reference combined with deep structural family inheritance and formal re-structuring of the systems over time
  • Forkel, S. J., & Catani, M. (2018). Structural Neuroimaging. In A. De Groot, & P. Hagoort (Eds.), Research Methods in Psycholinguistics and the Neurobiology of Language: A Practical Guide (pp. 288-308). Hoboken: Wiley. doi:10.1002/9781394259762.ch15.

    Abstract

    Structural imaging based on computerized tomography (CT) and magnetic resonance imaging (MRI) has progressively replaced traditional post‐mortem studies in the process of identifying the neuroanatomical basis of language. In the clinical setting, the information provided by structural imaging has been used to confirm the exact diagnosis and formulate an individualized treatment plan. In the research arena, neuroimaging has permitted to understand neuroanatomy at the individual and group level. The possibility to obtain quantitative measures of lesions has improved correlation analyses between severity of symptoms, lesion load, and lesion location. More recently, the development of structural imaging based on diffusion MRI has provided valid solutions to two major limitations of more conventional imaging. In stroke patients, diffusion can visualize early changes due to a stroke that are otherwise not detectable with more conventional structural imaging, with important implications for the clinical management of acute stroke patients. Beyond the sensitivity to early changes, diffusion imaging tractography presents the possibility of visualizing the trajectories of individual white matter pathways connecting distant regions. A pathway analysis based on tractography is offering a new perspective in neurolinguistics. First, it permits to formulate new anatomical models of language function in the healthy brain and allows to directly test these models in the human population without any reliance on animal models. Second, by defining the exact location of the damage to specific white matter connections we can understand the contribution of different mechanisms to the emergence of language deficits (e.g., cortical versus disconnection mechanisms). Finally, a better understanding of the anatomical variability of different language networks is helping to identify new anatomical predictors of language recovery. In this chapter we will focus on the principles of structural MRI and, in particular, diffusion imaging and tractography and present examples of how these methods have informed our understanding of variance in language performances in the healthy brain and language deficits in patient populations.
  • 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., Gerstenkorn, G., & Scherp, A. (2018). A case study of closed-domain response suggestion with limited training data. In M. Elloumi, M. Granitzer, A. Hameurlain, C. Seifert, B. Stein, A. Min Tjoa, & R. Wagner (Eds.), Database and Expert Systems Applications: DEXA 2018 International Workshops, BDMICS, BIOKDD, and TIR, Regensburg, Germany, September 3–6, 2018, Proceedings (pp. 218-229). Cham, Switzerland: Springer.

    Abstract

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

    Abstract

    We present multi-modal adversarial autoencoders for recommendation and evaluate them on two different tasks: citation recommendation and subject label recommendation. We analyze the effects of adversarial regularization, sparsity, and different input modalities. By conducting 408 experiments, we show that adversarial regularization consistently improves the performance of autoencoders for recommendation. We demonstrate, however, that the two tasks differ in the semantics of item co-occurrence in the sense that item co-occurrence resembles relatedness in case of citations, yet implies diversity in case of subject labels. Our results reveal that supplying the partial item set as input is only helpful, when item co-occurrence resembles relatedness. When facing a new recommendation task it is therefore crucial to consider the semantics of item co-occurrence for the choice of an appropriate model.
  • 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
  • Gingras, B., Honing, H., Peretz, I., Trainor, L. J., & Fisher, S. E. (2018). Defining the biological bases of individual differences in musicality. In H. Honing (Ed.), The origins of musicality (pp. 221-250). Cambridge, MA: MIT Press.
  • Gordon, P. C., Lowder, M. W., & Hoedemaker, R. S. (2016). Reading in normally aging adults. In H. Wright (Ed.), Cognitive-Linguistic Processes and Aging (pp. 165-192). Amsterdam: Benjamins. doi:10.1075/z.200.07gor.

    Abstract

    The activity of reading raises fundamental theoretical and practical questions about healthy cognitive aging. Reading relies greatly on knowledge of patterns of language and of meaning at the level of words and topics of text. Further, this knowledge must be rapidly accessed so that it can be coordinated with processes of perception, attention, memory and motor control that sustain skilled reading at rates of four-to-five words a second. As such, reading depends both on crystallized semantic intelligence which grows or is maintained through healthy aging, and on components of fluid intelligence which decline with age. Reading is important to older adults because it facilitates completion of everyday tasks that are essential to independent living. In addition, it entails the kind of active mental engagement that can preserve and deepen the cognitive reserve that may mitigate the negative consequences of age-related changes in the brain. This chapter reviews research on the front end of reading (word recognition) and on the back end of reading (text memory) because both of these abilities are surprisingly robust to declines associated with cognitive aging. For word recognition, that robustness is surprising because rapid processing of the sort found in reading is usually impaired by aging; for text memory, it is surprising because other types of episodic memory performance (e.g., paired associates) substantially decline in aging. These two otherwise quite different levels of reading comprehension remain robust because they draw on the knowledge of language that older adults gain through a life-time of experience with language.
  • Hagoort, P. (2016). MUC (Memory, Unification, Control): A Model on the Neurobiology of Language Beyond Single Word Processing. In G. Hickok, & S. Small (Eds.), Neurobiology of language (pp. 339-347). Amsterdam: Elsever. doi:10.1016/B978-0-12-407794-2.00028-6.

    Abstract

    A neurobiological model of language is discussed that overcomes the shortcomings of the classical Wernicke-Lichtheim-Geschwind model. It is based on a subdivision of language processing into three components: Memory, Unification, and Control. The functional components as well as the neurobiological underpinnings of the model are discussed. In addition, the need for extension beyond the classical core regions for language is shown. Attentional networks as well as networks for inferential processing are crucial to realize language comprehension beyond single word processing and beyond decoding propositional content.
  • Hagoort, P. (2016). Zij zijn ons brein. In J. Brockman (Ed.), Machines die denken: Invloedrijke denkers over de komst van kunstmatige intelligentie (pp. 184-186). Amsterdam: Maven Publishing.
  • Hammarström, H. (2018). Language isolates in the New Guinea region. In L. Campbell (Ed.), Language Isolates (pp. 287-322). London: Routledge.
  • Harmon, Z., & Kapatsinski, V. (2016). Fuse to be used: A weak cue’s guide to attracting attention. In A. Papafragou, D. Grodner, D. Mirman, & J. Trueswell (Eds.), Proceedings of the 38th Annual Meeting of the Cognitive Science Society (CogSci 2016). Austin, TX: Cognitive Science Society (pp. 520-525). Austin, TX: Cognitive Science Society.

    Abstract

    Several studies examined cue competition in human learning by testing learners on a combination of conflicting cues rooting for different outcomes, with each cue perfectly predicting its outcome. A common result has been that learners faced with cue conflict choose the outcome associated with the rare cue (the Inverse Base Rate Effect, IBRE). Here, we investigate cue competition including IBRE with sentences containing cues to meanings in a visual world. We do not observe IBRE. Instead we find that position in the sentence strongly influences cue salience. Faced with conflict between an initial cue and a non-initial cue, learners choose the outcome associated with the initial cue, whether frequent or rare. However, a frequent configuration of non-initial cues that are not sufficiently salient on their own can overcome a competing salient initial cue rooting for a different meaning. This provides a possible explanation for certain recurring patterns in language change.
  • Harmon, Z., & Kapatsinski, V. (2016). Determinants of lengths of repetition disfluencies: Probabilistic syntactic constituency in speech production. In R. Burkholder, C. Cisneros, E. R. Coppess, J. Grove, E. A. Hanink, H. McMahan, C. Meyer, N. Pavlou, Ö. Sarıgül, A. R. Singerman, & A. Zhang (Eds.), Proceedings of the Fiftieth Annual Meeting of the Chicago Linguistic Society (pp. 237-248). Chicago: Chicago Linguistic Society.
  • 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.
  • Hoey, E., & Kendrick, K. H. (2018). Conversation analysis. In A. M. B. De Groot, & P. Hagoort (Eds.), Research methods in psycholinguistics and the neurobiology of language: A practical guide (pp. 151-173). Hoboken: Wiley.

    Abstract

    Conversation Analysis (CA) is an inductive, micro-analytic, and predominantly qualitative
    method for studying human social interactions. This chapter describes and illustrates the basic
    methods of CA. We first situate the method by describing its sociological foundations, key areas
    of analysis, and particular approach in using naturally occurring data. The bulk of the chapter is
    devoted to practical explanations of the typical conversation analytic process for collecting data
    and producing an analysis. We analyze a candidate interactional practice – the assessmentimplicative
    interrogative – using real data extracts as a demonstration of the method, explicitly
    laying out the relevant questions and considerations for every stage of an analysis. The chapter
    concludes with some discussion of quantitative approaches to conversational interaction, and
    links between CA and psycholinguistic concerns
  • 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.
  • Indefrey, P. (2018). The relationship between syntactic production and comprehension. In S.-A. Rueschemeyer, & M. G. Gaskell (Eds.), The Oxford Handbook of Psycholinguistics (2nd ed., pp. 486-505). Oxford: Oxford University Press.

    Abstract

    This chapter deals with the question of whether there is one syntactic system that is shared by language production and comprehension or whether there are two separate systems. It first discusses arguments in favor of one or the other option and then presents the current evidence on the brain structures involved in sentence processing. The results of meta-analyses of numerous neuroimaging studies suggest that there is one system consisting of functionally distinct cortical regions: the dorsal part of Broca’s area subserving compositional syntactic processing; the ventral part of Broca’s area subserving compositional semantic processing; and the left posterior temporal cortex (Wernicke’s area) subserving the retrieval of lexical syntactic and semantic information. Sentence production, the comprehension of simple and complex sentences, and the parsing of sentences containing grammatical violations differ with respect to the recruitment of these functional components.
  • 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. (2018). Genetic biases affecting language: What do computer models and experimental approaches suggest? In T. Poibeau, & A. Villavicencio (Eds.), Language, Cognition and Computational Models (pp. 256-288). Cambridge: Cambridge University Press.

    Abstract

    Computer models of cultural evolution have shown language properties emerging on interacting agents with a brain that lacks dedicated, nativist language modules. Notably, models using Bayesian agents provide a precise specification of (extra-)liguististic factors (e.g., genetic) that shape language through iterated learning (biases on language), and demonstrate that weak biases get expressed more strongly over time (bias amplification). Other models attempt to lessen assumption on agents’ innate predispositions even more, and emphasize self-organization within agents, highlighting glossogenesis (the development of language from a nonlinguistic state). Ultimately however, one also has to recognize that biology and culture are strongly interacting, forming a coevolving system. As such, computer models show that agents might (biologically) evolve to a state predisposed to language adaptability, where (culturally) stable language features might get assimilated into the genome via Baldwinian niche construction. In summary, while many questions about language evolution remain unanswered, it is clear that it is not to be completely understood from a purely biological, cognitivist perspective. Language should be regarded as (partially) emerging on the social interactions between large populations of speakers. In this context, agent models provide a sound approach to investigate the complex dynamics of genetic biasing on language and speech
  • 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.
  • 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.
  • 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
  • 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
  • De Kovel, C. G. F., & Fisher, S. E. (2018). Molecular genetic methods. In A. M. B. De Groot, & P. Hagoort (Eds.), Research methods in psycholinguistics and the neurobiology of language: A practical guide (pp. 330-353). Hoboken: Wiley.
  • 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. (2016). Localism versus holism. Historical origins of studying language in the brain. In R. Rubens, & M. Van Dijk (Eds.), Sartoniana vol. 29 (pp. 37-60). Ghent: Ghent University.
  • Levelt, W. J. M. (2016). The first golden age of psycholinguistics 1865-World War I. In R. Rubens, & M. Van Dyck (Eds.), Sartoniana vol. 29 (pp. 15-36). Ghent: Ghent University.
  • Levelt, W. J. M., & De Swaan, A. (2016). Levensbericht Nico Frijda. In Koninklijke Nederlandse Akademie van Wetenschappen (Ed.), Levensberichten en herdenkingen 2016 (pp. 16-25). Amsterdam: KNAW.
  • Levelt, W. J. M. (1962). Motion breaking and the perception of causality. In A. Michotte (Ed.), Causalité, permanence et réalité phénoménales: Etudes de psychologie expérimentale (pp. 244-258). Louvain: Publications Universitaires.
  • Levelt, W. J. M., & Plomp, R. (1962). Musical consonance and critical bandwidth. In Proceedings of the 4th International Congress Acoustics (pp. 55-55).
  • Levelt, W. J. M., & Plomp, K. (1968). The appreciation of musical intervals. In J. M. M. Aler (Ed.), Proceedings of the fifth International Congress of Aesthetics, Amsterdam 1964 (pp. 901-904). The Hague: Mouton.
  • Levelt, W. J. M. (1966). The perceptual conflict in binocular rivalry. In M. A. Bouman (Ed.), Studies in perception: Dedicated to M.A. Bouman (pp. 47-60). Soesterberg: Institute for Perception RVO-TNO.
  • Levinson, S. C. (2016). Language and mind: Let's get the issues straight! In S. D. Blum (Ed.), Making sense of language: Readings in culture and communication [3rd ed.] (pp. 68-80). Oxford: Oxford University Press.
  • Levinson, S. C. (2018). Introduction: Demonstratives: Patterns in diversity. In S. C. Levinson, S. Cutfield, M. Dunn, N. J. Enfield, & S. Meira (Eds.), Demonstratives in cross-linguistic perspective (pp. 1-42). Cambridge: Cambridge University Press.
  • Levinson, S. C. (2016). The countable singulare tantum. In A. Reuneker, R. Boogaart, & S. Lensink (Eds.), Aries netwerk: Een constructicon (pp. 145-146). Leiden: Leiden University.
  • Levinson, S. C. (2018). Yélî Dnye: Demonstratives in the language of Rossel Island, Papua New Guinea. In S. C. Levinson, S. Cutfield, M. Dunn, N. J. Enfield, & S. Meira (Eds.), Demonstratives in cross-linguistic perspective (pp. 318-342). Cambridge: Cambridge University Press.
  • 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., 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. (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%.
  • Majid, A. (2018). Cultural factors shape olfactory language [Reprint]. In D. Howes (Ed.), Senses and Sensation: Critical and Primary Sources. Volume 3 (pp. 307-310). London: Bloomsbury Publishing.
  • Majid, A. (2018). Language and cognition. In H. Callan (Ed.), The International Encyclopedia of Anthropology. Hoboken: John Wiley & Sons Ltd.

    Abstract

    What is the relationship between the language we speak and the way we think? Researchers working at the interface of language and cognition hope to understand the complex interplay between linguistic structures and the way the mind works. This is thorny territory in anthropology and its closely allied disciplines, such as linguistics and psychology.

    Additional information

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  • Majid, A. (2016). Was wir von anderen Kulturen über den Geruchsinn lernen können. In Museum Tinguely (Ed.), Belle Haleine – Der Duft der Kunst. Interdisziplinäres Symposium (pp. 73-79). Heidelberg: Kehrer.
  • Majid, A. (2016). What other cultures can tell us about the sense of smell. In Museum Tinguely (Ed.), Belle haleine - the scent of art: interdisciplinary symposium (pp. 72-77). Heidelberg: Kehrer.

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