Publications

Displaying 201 - 237 of 237
  • Siahaan, P., & Wijaya Rajeg, G. P. (2023). Multimodal language use in Indonesian: Recurrent gestures associated with negation. In W. Pouw, J. Trujillo, H. R. Bosker, L. Drijvers, M. Hoetjes, J. Holler, S. Kadava, L. Van Maastricht, E. Mamus, & A. Ozyurek (Eds.), Gesture and Speech in Interaction (GeSpIn) Conference. doi:10.17617/2.3527196.

    Abstract

    This paper presents research findings on manual gestures
    associated with negation in Indonesian, utilizing data sourced
    from talk shows available on YouTube. The study reveals that
    Indonesian speakers employ six recurrent negation gestures,
    which have been observed in various languages worldwide.
    This suggests that gestures exhibiting a stable form-meaning
    relationship and recurring frequently in relation to negation are
    prevalent around the globe, although their distribution may
    differ across cultures and languages. Furthermore, the paper
    demonstrates that negation gestures are not strictly tied to
    verbal negation. Overall, the aim of this paper is to contribute
    to a deeper understanding of the conventional usage and cross-
    linguistic distribution of recurrent gestures.
  • Slonimska, A., & Roberts, S. G. (2017). A case for systematic sound symbolism in pragmatics:The role of the first phoneme in question prediction in context. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (CogSci 2017) (pp. 1090-1095). Austin, TX: Cognitive Science Society.

    Abstract

    Turn-taking in conversation is a cognitively demanding process that proceeds rapidly due to interlocutors utilizing a range of cues
    to aid prediction. In the present study we set out to test recent claims that content question words (also called wh-words) sound similar within languages as an adaptation to help listeners predict
    that a question is about to be asked. We test whether upcoming questions can be predicted based on the first phoneme of a turn and the prior context. We analyze the Switchboard corpus of English
    by means of a decision tree to test whether /w/ and /h/ are good statistical cues of upcoming questions in conversation. Based on the results, we perform a controlled experiment to test whether
    people really use these cues to recognize questions. In both studies
    we show that both the initial phoneme and the sequential context help predict questions. This contributes converging evidence that elements of languages adapt to pragmatic pressures applied during
    conversation.
  • Smith, A. C., Monaghan, P., & Huettig, F. (2013). Modelling the effects of formal literacy training on language mediated visual attention. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Meeting of the Cognitive Science Society (CogSci 2013) (pp. 3420-3425). Austin, TX: Cognitive Science Society.

    Abstract

    Recent empirical evidence suggests that language-mediated eye gaze is partly determined by level of formal literacy training. Huettig, Singh and Mishra (2011) showed that high-literate individuals' eye gaze was closely time locked to phonological overlap between a spoken target word and items presented in a visual display. In contrast, low-literate individuals' eye gaze was not related to phonological overlap, but was instead strongly influenced by semantic relationships between items. Our present study tests the hypothesis that this behavior is an emergent property of an increased ability to extract phonological structure from the speech signal, as in the case of high-literates, with low-literates more reliant on more coarse grained structure. This hypothesis was tested using a neural network model, that integrates linguistic information extracted from the speech signal with visual and semantic information within a central resource. We demonstrate that contrasts in fixation behavior similar to those observed between high and low literates emerge when models are trained on speech signals of contrasting granularity.
  • Speed, L., & Majid, A. (2018). Music and odor in harmony: A case of music-odor synaesthesia. 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. 2527-2532). Austin, TX: Cognitive Science Society.

    Abstract

    We report an individual with music-odor synaesthesia who experiences automatic and vivid odor sensations when she hears music. S’s odor associations were recorded on two days, and compared with those of two control participants. Overall, S produced longer descriptions, and her associations were of multiple odors at once, in comparison to controls who typically reported a single odor. Although odor associations were qualitatively different between S and controls, ratings of the consistency of their descriptions did not differ. This demonstrates that crossmodal associations between music and odor exist in non-synaesthetes too. We also found that S is better at discriminating between odors than control participants, and is more likely to experience emotion, memories and evaluations triggered by odors, demonstrating the broader impact of her synaesthesia.

    Additional information

    link to conference website
  • Stanojevic, M., & Alhama, R. G. (2017). Neural discontinuous constituency parsing. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (pp. 1666-1676). Association for Computational Linguistics.

    Abstract

    One of the most pressing issues in dis-
    continuous constituency transition-based
    parsing is that the relevant information for
    parsing decisions could be located in any
    part of the stack or the buffer. In this pa-
    per, we propose a solution to this prob-
    lem by replacing the structured percep-
    tron model with a recursive neural model
    that computes a global representation of
    the configuration, therefore allowing even
    the most remote parts of the configura-
    tion to influence the parsing decisions. We
    also provide a detailed analysis of how
    this representation should be built out of
    sub-representations of its core elements
    (words, trees and stack). Additionally, we
    investigate how different types of swap or-
    acles influence the results. Our model is
    the first neural discontinuous constituency
    parser, and it outperforms all the previ-
    ously published models on three out of
    four datasets while on the fourth it obtains
    second place by a tiny difference.

    Additional information

    http://aclweb.org/anthology/D17-1174
  • Stern, G. (2023). On embodied use of recognitional demonstratives. In W. Pouw, J. Trujillo, H. R. Bosker, L. Drijvers, M. Hoetjes, J. Holler, S. Kadava, L. Van Maastricht, E. Mamus, & A. Ozyurek (Eds.), Gesture and Speech in Interaction (GeSpIn) Conference. doi:10.17617/2.3527204.

    Abstract

    This study focuses on embodied uses of recognitional
    demonstratives. While multimodal conversation analytic
    studies have shown how gesture and speech interact in the
    elaboration of exophoric references, little attention has been
    given to the multimodal configuration of other types of
    referential actions. Based on a video-recorded corpus of
    professional meetings held in French, this qualitative study
    shows that a subtype of deictic references, namely recognitional
    references, are frequently associated with iconic gestures, thus
    challenging the traditional distinction between exophoric and
    endophoric uses of deixis.
  • Stivers, T., & Sidnell, J. (Eds.). (2013). The handbook on conversation analysis. Malden, MA: Wiley-Blackwell.

    Abstract

    Presenting a comprehensive, state-of-the-art overview of theoretical and descriptive research in the field, The Handbook of Conversation Analysis brings together contributions by leading international experts to provide an invaluable information resource and reference for scholars of social interaction across the areas of conversation analysis, discourse analysis, linguistic anthropology, interpersonal communication, discursive psychology and sociolinguistics. Ideal as an introduction to the field for upper level undergraduates and as an in-depth review of the latest developments for graduate level students and established scholars Five sections outline the history and theory, methods, fundamental concepts, and core contexts in the study of conversation, as well as topics central to conversation analysis Written by international conversation analysis experts, the book covers a wide range of topics and disciplines, from reviewing underlying structures of conversation, to describing conversation analysis' relationship to anthropology, communication, linguistics, psychology, and sociology
  • Sumer, B., Grabitz, C., & Küntay, A. (2017). Early produced signs are iconic: Evidence from Turkish Sign Language. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (CogSci 2017) (pp. 3273-3278). Austin, TX: Cognitive Science Society.

    Abstract

    Motivated form-meaning mappings are pervasive in sign languages, and iconicity has recently been shown to facilitate sign learning from early on. This study investigated the role of iconicity for language acquisition in Turkish Sign Language (TID). Participants were 43 signing children (aged 10 to 45 months) of deaf parents. Sign production ability was recorded using the adapted version of MacArthur Bates Communicative Developmental Inventory (CDI) consisting of 500 items for TID. Iconicity and familiarity ratings for a subset of 104 signs were available. Our results revealed that the iconicity of a sign was positively correlated with the percentage of children producing a sign and that iconicity significantly predicted the percentage of children producing a sign, independent of familiarity or phonological complexity. Our results are consistent with previous findings on sign language acquisition and provide further support for the facilitating effect of iconic form-meaning mappings in sign learning.
  • Sumner, M., Kurumada, C., Gafter, R., & Casillas, M. (2013). Phonetic variation and the recognition of words with pronunciation variants. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Meeting of the Cognitive Science Society (CogSci 2013) (pp. 3486-3492). Austin, TX: Cognitive Science Society.
  • Ten Bosch, L., Ernestus, M., & Boves, L. (2018). Analyzing reaction time sequences from human participants in auditory experiments. In Proceedings of Interspeech 2018 (pp. 971-975). doi:10.21437/Interspeech.2018-1728.

    Abstract

    Sequences of reaction times (RT) produced by participants in an experiment are not only influenced by the stimuli, but by many other factors as well, including fatigue, attention, experience, IQ, handedness, etc. These confounding factors result in longterm effects (such as a participant’s overall reaction capability) and in short- and medium-time fluctuations in RTs (often referred to as ‘local speed effects’). Because stimuli are usually presented in a random sequence different for each participant, local speed effects affect the underlying ‘true’ RTs of specific trials in different ways across participants. To be able to focus statistical analysis on the effects of the cognitive process under study, it is necessary to reduce the effect of confounding factors as much as possible. In this paper we propose and compare techniques and criteria for doing so, with focus on reducing (‘filtering’) the local speed effects. We show that filtering matters substantially for the significance analyses of predictors in linear mixed effect regression models. The performance of filtering is assessed by the average between-participant correlation between filtered RT sequences and by Akaike’s Information Criterion, an important measure of the goodness-of-fit of linear mixed effect regression models.
  • Ten Bosch, L., & Boves, L. (2018). Information encoding by deep neural networks: what can we learn? In Proceedings of Interspeech 2018 (pp. 1457-1461). doi:10.21437/Interspeech.2018-1896.

    Abstract

    The recent advent of deep learning techniques in speech tech-nology and in particular in automatic speech recognition hasyielded substantial performance improvements. This suggeststhat deep neural networks (DNNs) are able to capture structurein speech data that older methods for acoustic modeling, suchas Gaussian Mixture Models and shallow neural networks failto uncover. In image recognition it is possible to link repre-sentations on the first couple of layers in DNNs to structuralproperties of images, and to representations on early layers inthe visual cortex. This raises the question whether it is possi-ble to accomplish a similar feat with representations on DNNlayers when processing speech input. In this paper we presentthree different experiments in which we attempt to untanglehow DNNs encode speech signals, and to relate these repre-sentations to phonetic knowledge, with the aim to advance con-ventional phonetic concepts and to choose the topology of aDNNs more efficiently. Two experiments investigate represen-tations formed by auto-encoders. A third experiment investi-gates representations on convolutional layers that treat speechspectrograms as if they were images. The results lay the basisfor future experiments with recursive networks.
  • Ten Bosch, L., Boves, L., & Ernestus, M. (2017). The recognition of compounds: A computational account. In Proceedings of Interspeech 2017 (pp. 1158-1162). doi:10.21437/Interspeech.2017-1048.

    Abstract

    This paper investigates the processes in comprehending spoken noun-noun compounds, using data from the BALDEY database. BALDEY contains lexicality judgments and reaction times (RTs) for Dutch stimuli for which also linguistic information is included. Two different approaches are combined. The first is based on regression by Dynamic Survival Analysis, which models decisions and RTs as a consequence of the fact that a cumulative density function exceeds some threshold. The parameters of that function are estimated from the observed RT data. The second approach is based on DIANA, a process-oriented computational model of human word comprehension, which simulates the comprehension process with the acoustic stimulus as input. DIANA gives the identity and the number of the word candidates that are activated at each 10 ms time step.

    Both approaches show how the processes involved in comprehending compounds change during a stimulus. Survival Analysis shows that the impact of word duration varies during the course of a stimulus. The density of word and non-word hypotheses in DIANA shows a corresponding pattern with different regimes. We show how the approaches complement each other, and discuss additional ways in which data and process models can be combined.
  • Ten Bosch, L., Boves, L., & Ernestus, M. (2013). Towards an end-to-end computational model of speech comprehension: simulating a lexical decision task. In Proceedings of INTERSPEECH 2013: 14th Annual Conference of the International Speech Communication Association (pp. 2822-2826).

    Abstract

    This paper describes a computational model of speech comprehension that takes the acoustic signal as input and predicts reaction times as observed in an auditory lexical decision task. By doing so, we explore a new generation of end-to-end computational models that are able to simulate the behaviour of human subjects participating in a psycholinguistic experiment. So far, nearly all computational models of speech comprehension do not start from the speech signal itself, but from abstract representations of the speech signal, while the few existing models that do start from the acoustic signal cannot directly model reaction times as obtained in comprehension experiments. The main functional components in our model are the perception stage, which is compatible with the psycholinguistic model Shortlist B and is implemented with techniques from automatic speech recognition, and the decision stage, which is based on the linear ballistic accumulation decision model. We successfully tested our model against data from 20 participants performing a largescale auditory lexical decision experiment. Analyses show that the model is a good predictor for the average judgment and reaction time for each word.
  • Thompson, B., & Lupyan, G. (2018). Automatic estimation of lexical concreteness in 77 languages. 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. 1122-1127). Austin, TX: Cognitive Science Society.

    Abstract

    We estimate lexical Concreteness for millions of words across 77 languages. Using a simple regression framework, we combine vector-based models of lexical semantics with experimental norms of Concreteness in English and Dutch. By applying techniques to align vector-based semantics across distinct languages, we compute and release Concreteness estimates at scale in numerous languages for which experimental norms are not currently available. This paper lays out the technique and its efficacy. Although this is a difficult dataset to evaluate immediately, Concreteness estimates computed from English correlate with Dutch experimental norms at $\rho$ = .75 in the vocabulary at large, increasing to $\rho$ = .8 among Nouns. Our predictions also recapitulate attested relationships with word frequency. The approach we describe can be readily applied to numerous lexical measures beyond Concreteness
  • Thompson, B., Roberts, S., & Lupyan, G. (2018). Quantifying semantic similarity across languages. 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. 2551-2556). Austin, TX: Cognitive Science Society.

    Abstract

    Do all languages convey semantic knowledge in the same way? If language simply mirrors the structure of the world, the answer should be a qualified “yes”. If, however, languages impose structure as much as reflecting it, then even ostensibly the “same” word in different languages may mean quite different things. We provide a first pass at a large-scale quantification of cross-linguistic semantic alignment of approximately 1000 meanings in 55 languages. We find that the translation equivalents in some domains (e.g., Time, Quantity, and Kinship) exhibit high alignment across languages while the structure of other domains (e.g., Politics, Food, Emotions, and Animals) exhibits substantial cross-linguistic variability. Our measure of semantic alignment correlates with known phylogenetic distances between languages: more phylogenetically distant languages have less semantic alignment. We also find semantic alignment to correlate with cultural distances between societies speaking the languages, suggesting a rich co-adaptation of language and culture even in domains of experience that appear most constrained by the natural world
  • Timmer, K., Ganushchak, L. Y., Mitlina, Y., & Schiller, N. O. (2013). Choosing first or second language phonology in 125 ms [Abstract]. Journal of Cognitive Neuroscience, 25 Suppl., 164.

    Abstract

    We are often in a bilingual situation (e.g., overhearing a conversation in the train). We investigated whether first (L1) and second language (L2) phonologies are automatically activated. A masked priming paradigm was used, with Russian words as targets and either Russian or English words as primes. Event-related potentials (ERPs) were recorded while Russian (L1) – English (L2) bilinguals read aloud L1 target words (e.g. РЕЙС /reis/ ‘fl ight’) primed with either L1 (e.g. РАНА /rana/ ‘wound’) or L2 words (e.g. PACK). Target words were read faster when they were preceded by phonologically related L1 primes but not by orthographically related L2 primes. ERPs showed orthographic priming in the 125-200 ms time window. Thus, both L1 and L2 phonologies are simultaneously activated during L1 reading. The results provide support for non-selective models of bilingual reading, which assume automatic activation of the non-target language phonology even when it is not required by the task.
  • Tourtouri, E. N., Delogu, F., & Crocker, M. W. (2018). Specificity and entropy reduction in situated referential processing. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (CogSci 2017) (pp. 3356-3361). Austin: Cognitive Science Society.

    Abstract

    In situated communication, reference to an entity in the shared visual context can be established using eitheranexpression that conveys precise (minimally specified) or redundant (over-specified) information. There is, however, along-lasting debate in psycholinguistics concerningwhether the latter hinders referential processing. We present evidence from an eyetrackingexperiment recordingfixations as well asthe Index of Cognitive Activity –a novel measure of cognitive workload –supporting the view that over-specifications facilitate processing. We further present originalevidence that, above and beyond the effect of specificity,referring expressions thatuniformly reduce referential entropyalso benefitprocessing
  • Tsoukala, C., Frank, S. L., & Broersma, M. (2017). “He's pregnant": Simulating the confusing case of gender pronoun errors in L2 English. In Proceedings of the 39th Annual Meeting of the Cognitive Science Society (CogSci 2017) (pp. 3392-3397). Austin, TX, USA: Cognitive Science Society.

    Abstract

    Even advanced Spanish speakers of second language English tend to confuse the pronouns ‘he’ and ‘she’, often without even noticing their mistake (Lahoz, 1991). A study by AntónMéndez (2010) has indicated that a possible reason for this error is the fact that Spanish is a pro-drop language. In order to test this hypothesis, we used an extension of Dual-path (Chang, 2002), a computational cognitive model of sentence production, to simulate two models of bilingual speech production of second language English. One model had Spanish (ES) as a native language, whereas the other learned a Spanish-like language that used the pronoun at all times (non-pro-drop Spanish, NPD_ES). When tested on L2 English sentences, the bilingual pro-drop Spanish model produced significantly more gender pronoun errors, confirming that pronoun dropping could indeed be responsible for the gender confusion in natural language use as well.
  • Uhrig, P., Payne, E., Pavlova, I., Burenko, I., Dykes, N., Baltazani, M., Burrows, E., Hale, S., Torr, P., & Wilson, A. (2023). Studying time conceptualisation via speech, prosody, and hand gesture: Interweaving manual and computational methods of analysis. In W. Pouw, J. Trujillo, H. R. Bosker, L. Drijvers, M. Hoetjes, J. Holler, S. Kadava, L. Van Maastricht, E. Mamus, & A. Ozyurek (Eds.), Gesture and Speech in Interaction (GeSpIn) Conference. doi:10.17617/2.3527220.

    Abstract

    This paper presents a new interdisciplinary methodology for the
    analysis of future conceptualisations in big messy media data.
    More specifically, it focuses on the depictions of post-Covid
    futures by RT during the pandemic, i.e. on data which are of
    interest not just from the perspective of academic research but
    also of policy engagement. The methodology has been
    developed to support the scaling up of fine-grained data-driven
    analysis of discourse utterances larger than individual lexical
    units which are centred around ‘will’ + the infinitive. It relies
    on the true integration of manual analytical and computational
    methods and tools in researching three modalities – textual,
    prosodic1, and gestural. The paper describes the process of
    building a computational infrastructure for the collection and
    processing of video data, which aims to empower the manual
    analysis. It also shows how manual analysis can motivate the
    development of computational tools. The paper presents
    individual computational tools to demonstrate how the
    combination of human and machine approaches to analysis can
    reveal new manifestations of cohesion between gesture and
    prosody. To illustrate the latter, the paper shows how the
    boundaries of prosodic units can work to help determine the
    boundaries of gestural units for future conceptualisations.
  • Uluşahin, O., Bosker, H. R., McQueen, J. M., & Meyer, A. S. (2023). No evidence for convergence to sub-phonemic F2 shifts in shadowing. In R. Skarnitzl, & J. Volín (Eds.), Proceedings of the 20th International Congress of the Phonetic Sciences (ICPhS 2023) (pp. 96-100). Prague: Guarant International.

    Abstract

    Over the course of a conversation, interlocutors sound more and more like each other in a process called convergence. However, the automaticity and grain size of convergence are not well established. This study therefore examined whether female native Dutch speakers converge to large yet sub-phonemic shifts in the F2 of the vowel /e/. Participants first performed a short reading task to establish baseline F2s for the vowel /e/, then shadowed 120 target words (alongside 360 fillers) which contained one instance of a manipulated vowel /e/ where the F2 had been shifted down to that of the vowel /ø/. Consistent exposure to large (sub-phonemic) downward shifts in F2 did not result in convergence. The results raise issues for theories which view convergence as a product of automatic integration between perception and production.
  • Ünal, E., & Papafragou, A. (2013). Linguistic and conceptual representations of inference as a knowledge source. In S. Baiz, N. Goldman, & R. Hawkes (Eds.), Proceedings of the 37th Annual Boston University Conference on Language Development (BUCLD 37) (pp. 433-443). Boston: Cascadilla Press.
  • Vagliano, I., Galke, L., Mai, F., & Scherp, A. (2018). Using adversarial autoencoders for multi-modal automatic playlist continuation. In C.-W. Chen, P. Lamere, M. Schedl, & H. Zamani (Eds.), RecSys Challenge '18: Proceedings of the ACM Recommender Systems Challenge 2018 (pp. 5.1-5.6). New York: ACM. doi:10.1145/3267471.3267476.

    Abstract

    The task of automatic playlist continuation is generating a list of recommended tracks that can be added to an existing playlist. By suggesting appropriate tracks, i. e., songs to add to a playlist, a recommender system can increase the user engagement by making playlist creation easier, as well as extending listening beyond the end of current playlist. The ACM Recommender Systems Challenge 2018 focuses on such task. Spotify released a dataset of playlists, which includes a large number of playlists and associated track listings. Given a set of playlists from which a number of tracks have been withheld, the goal is predicting the missing tracks in those playlists. We participated in the challenge as the team Unconscious Bias and, in this paper, we present our approach. We extend adversarial autoencoders to the problem of automatic playlist continuation. We show how multiple input modalities, such as the playlist titles as well as track titles, artists and albums, can be incorporated in the playlist continuation task.
  • Van Dooren, A., Dieuleveut, A., Cournane, A., & Hacquard, V. (2017). Learning what must and can must and can mean. In A. Cremers, T. Van Gessel, & F. Roelofsen (Eds.), Proceedings of the 21st Amsterdam Colloquium (pp. 225-234). Amsterdam: ILLC.

    Abstract

    This corpus study investigates how children figure out that functional modals
    like must can express various flavors of modality. We examine how modality is
    expressed in speech to and by children, and find that the way speakers use
    modals may obscure their polysemy. Yet, children eventually figure it out. Our
    results suggest that some do before age 3. We show that while root and
    epistemic flavors are not equally well-represented in the input, there are robust
    correlations between flavor and aspect, which learners could exploit to discover
    modal polysemy.
  • Van Dooren, A. (2017). Dutch must more structure. In A. Lamont, & K. Tetzloff (Eds.), NELS 47: Proceedings of the Forty-Seventh Annual Meeting of the North East Linguistic Society (pp. 165-175). Amherst: GLSA.
  • Van Valin Jr., R. D. (2000). Focus structure or abstract syntax? A role and reference grammar account of some ‘abstract’ syntactic phenomena. In Z. Estrada Fernández, & I. Barreras Aguilar (Eds.), Memorias del V Encuentro Internacional de Lingüística en el Noroeste: (2 v.) Estudios morfosintácticos (pp. 39-62). Hermosillo: Editorial Unison.
  • Van Putten, S. (2013). The meaning of the Avatime additive particle tsye. In M. Balbach, L. Benz, S. Genzel, M. Grubic, A. Renans, S. Schalowski, M. Stegenwallner, & A. Zeldes (Eds.), Information structure: Empirical perspectives on theory (pp. 55-74). Potsdam: Universitätsverlag Potsdam. Retrieved from http://nbn-resolving.de/urn/resolver.pl?urn=urn:nbn:de:kobv:517-opus-64804.
  • Vernes, S. C. (2018). Vocal learning in bats: From genes to behaviour. 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. 516-518). Toruń, Poland: NCU Press. doi:10.12775/3991-1.128.
  • Vogel, C., Koutsombogera, M., Murat, A. C., Khosrobeigi, Z., & Ma, X. (2023). Gestural linguistic context vectors encode gesture meaning. In W. Pouw, J. Trujillo, H. R. Bosker, L. Drijvers, M. Hoetjes, J. Holler, S. Kadava, L. Van Maastricht, E. Mamus, & A. Ozyurek (Eds.), Gesture and Speech in Interaction (GeSpIn) Conference. doi:10.17617/2.3527176.

    Abstract

    Linguistic context vectors are adapted for measuring the linguistic contexts that accompany gestures and comparable co-linguistic behaviours. Focusing on gestural semiotic types, it is demonstrated that gestural linguistic context vectors carry information associated with gesture. It is suggested that these may be used to approximate gesture meaning in a similar manner to the approximation of word meaning by context vectors.
  • Von Holzen, K., & Bergmann, C. (2018). A Meta-Analysis of Infants’ Mispronunciation Sensitivity Development. 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. 1159-1164). Austin, TX: Cognitive Science Society.

    Abstract

    Before infants become mature speakers of their native language, they must acquire a robust word-recognition system which allows them to strike the balance between allowing some variation (mood, voice, accent) and recognizing variability that potentially changes meaning (e.g. cat vs hat). The current meta-analysis quantifies how the latter, termed mispronunciation sensitivity, changes over infants’ first three years, testing competing predictions of mainstream language acquisition theories. Our results show that infants were sensitive to mispronunciations, but accepted them as labels for target objects. Interestingly, and in contrast to predictions of mainstream theories, mispronunciation sensitivity was not modulated by infant age, suggesting that a sufficiently flexible understanding of native language phonology is in place at a young age.
  • von Stutterheim, C., & Flecken, M. (Eds.). (2013). Principles of information organization in L2 discourse [Special Issue]. International Review of Applied linguistics in Language Teaching (IRAL), 51(2).
  • Weber, A. (2000). Phonotactic and acoustic cues for word segmentation in English. In Proceedings of the 6th International Conference on Spoken Language Processing (ICSLP 2000) (pp. 782-785).

    Abstract

    This study investigates the influence of both phonotactic and acoustic cues on the segmentation of spoken English. Listeners detected embedded English words in nonsense sequences (word spotting). Words aligned with phonotactic boundaries were easier to detect than words without such alignment. Acoustic cues to boundaries could also have signaled word boundaries, especially when word onsets lacked phonotactic alignment. However, only one of several durational boundary cues showed a marginally significant correlation with response times (RTs). The results suggest that word segmentation in English is influenced primarily by phonotactic constraints and only secondarily by acoustic aspects of the speech signal.
  • Weber, A. (2000). The role of phonotactics in the segmentation of native and non-native continuous speech. In A. Cutler, J. M. McQueen, & R. Zondervan (Eds.), Proceedings of SWAP, Workshop on Spoken Word Access Processes. Nijmegen: MPI for Psycholinguistics.

    Abstract

    Previous research has shown that listeners make use of their knowledge of phonotactic constraints to segment speech into individual words. The present study investigates the influence of phonotactics when segmenting a non-native language. German and English listeners detected embedded English words in nonsense sequences. German listeners also had knowledge of English, but English listeners had no knowledge of German. Word onsets were either aligned with a syllable boundary or not, according to the phonotactics of the two languages. Words aligned with either German or English phonotactic boundaries were easier for German listeners to detect than words without such alignment. Responses of English listeners were influenced primarily by English phonotactic alignment. The results suggest that both native and non-native phonotactic constraints influence lexical segmentation of a non-native, but familiar, language.
  • Witteman, J., Karaseva, E., Schiller, N. O., & McQueen, J. M. (2023). What does successful L2 vowel acquisition depend on? A conceptual replication. In R. Skarnitzl, & J. Volín (Eds.), Proceedings of the 20th International Congress of the Phonetic Sciences (ICPhS 2023) (pp. 928-931). Prague: Guarant International.

    Abstract

    It has been suggested that individual variation in vowel compactness of the native language (L1) and the distance between L1 vowels and vowels in the second language (L2) predict successful L2 vowel acquisition. Moreover, general articulatory skills have been proposed to account for variation in vowel compactness. In the present work, we conceptually replicate a previous study to test these hypotheses with a large sample size, a new language pair and a
    new vowel pair. We find evidence that individual variation in L1 vowel compactness has opposing effects for two different vowels. We do not find evidence that individual variation in L1 compactness
    is explained by general articulatory skills. We conclude that the results found previously might be specific to sub-groups of L2 learners and/or specific sub-sets of vowel pairs.
  • Zhang, Y., & Yu, C. (2017). How misleading cues influence referential uncertainty in statistical cross-situational learning. In M. LaMendola, & J. Scott (Eds.), Proceedings of the 41st Annual Boston University Conference on Language Development (BUCLD 41) (pp. 820-833). Boston, MA: Cascadilla Press.
  • Zora, H., Tremblay, A. C., Gussenhoven, C., & Liu, F. (Eds.). (2023). Crosstalk between intonation and lexical tones: Linguistic, cognitive and neuroscience perspectives. Lausanne: Frontiers Media SA. doi:10.3389/978-2-8325-3301-7.
  • De Zubicaray, G., & Fisher, S. E. (Eds.). (2017). Genes, brain and language [Special Issue]. Brain and Language, 172.
  • De Zubicaray, G. I., Acheson, D. J., & Hartsuiker, R. J. (Eds.). (2013). Mind what you say - general and specific mechanisms for monitoring in speech production [Research topic] [Special Issue]. Frontiers in Human Neuroscience. Retrieved from http://www.frontiersin.org/human_neuroscience/researchtopics/mind_what_you_say_-_general_an/1197.

    Abstract

    Psycholinguistic research has typically portrayed speech production as a relatively automatic process. This is because when errors are made, they occur as seldom as one in every thousand words we utter. However, it has long been recognised that we need some form of control over what we are currently saying and what we plan to say. This capacity to both monitor our inner speech and self-correct our speech output has often been assumed to be a property of the language comprehension system. More recently, it has been demonstrated that speech production benefits from interfacing with more general cognitive processes such as selective attention, short-term memory (STM) and online response monitoring to resolve potential conflict and successfully produce the output of a verbal plan. The conditions and levels of representation according to which these more general planning, monitoring and control processes are engaged during speech production remain poorly understood. Moreover, there remains a paucity of information about their neural substrates, despite some of the first evidence of more general monitoring having come from electrophysiological studies of error related negativities (ERNs). While aphasic speech errors continue to be a rich source of information, there has been comparatively little research focus on instances of speech repair. The purpose of this Frontiers Research Topic is to provide a forum for researchers to contribute investigations employing behavioural, neuropsychological, electrophysiological, neuroimaging and virtual lesioning techniques. In addition, while the focus of the research topic is on novel findings, we welcome submission of computational simulations, review articles and methods papers.

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