Publications

Displaying 1 - 100 of 104
  • Alhama, R. G., & Zuidema, W. (2017). Segmentation as Retention and Recognition: the R&R model. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (CogSci 2017) (pp. 1531-1536). Austin, TX: Cognitive Science Society.

    Abstract

    We present the Retention and Recognition model (R&R), a probabilistic exemplar model that accounts for segmentation in Artificial Language Learning experiments. We show that R&R provides an excellent fit to human responses in three segmentation experiments with adults (Frank et al., 2010), outperforming existing models. Additionally, we analyze the results of the simulations and propose alternative explanations for the experimental findings.
  • Allen, S. E. M. (1997). Towards a discourse-pragmatic explanation for the subject-object asymmetry in early null arguments. In NET-Bulletin 1997 (pp. 1-16). Amsterdam, The Netherlands: Instituut voor Functioneel Onderzoek van Taal en Taalgebruik (IFOTT).
  • 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. (2017). Highly proficient bilinguals maintain language-specific pragmatic constraints on pronouns: Evidence from speech and gesture. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (CogSci 2017) (pp. 81-86). Austin, TX: Cognitive Science Society.

    Abstract

    The use of subject pronouns by bilingual speakers using both a pro-drop and a non-pro-drop language (e.g. Spanish heritage speakers in the USA) is a well-studied topic in research on cross-linguistic influence in language contact situations. Previous studies looking at bilinguals with different proficiency levels have yielded conflicting results on whether there is transfer from the non-pro-drop patterns to the pro-drop language. Additionally, previous research has focused on speech patterns only. In this paper, we study the two modalities of language, speech and gesture, and ask whether and how they reveal cross-linguistic influence on the use of subject pronouns in discourse. We focus on elicited narratives from heritage speakers of Turkish in the Netherlands, in both Turkish (pro-drop) and Dutch (non-pro-drop), as well as from monolingual control groups. The use of pronouns was not very common in monolingual Turkish narratives and was constrained by the pragmatic contexts, unlike in Dutch. Furthermore, Turkish pronouns were more likely to be accompanied by localized gestures than Dutch pronouns, presumably because pronouns in Turkish are pragmatically marked forms. We did not find any cross-linguistic influence in bilingual speech or gesture patterns, in line with studies (speech only) of highly proficient bilinguals. We therefore suggest that speech and gesture parallel each other not only in monolingual but also in bilingual production. Highly proficient heritage speakers who have been exposed to diverse linguistic and gestural patterns of each language from early on maintain monolingual patterns of pragmatic constraints on the use of pronouns multimodally.
  • Bauer, B. L. M. (1997). The adjective in Italic and Romance: Genetic or areal factors affecting word order patterns?”. In B. Palek (Ed.), Proceedings of LP'96: Typology: Prototypes, item orderings and universals (pp. 295-306). Prague: Charles 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., Tsuji, S., & Cristia, A. (2017). Top-down versus bottom-up theories of phonological acquisition: A big data approach. In Proceedings of Interspeech 2017 (pp. 2103-2107).

    Abstract

    Recent work has made available a number of standardized meta- analyses bearing on various aspects of infant language processing. We utilize data from two such meta-analyses (discrimination of vowel contrasts and word segmentation, i.e., recognition of word forms extracted from running speech) to assess whether the published body of empirical evidence supports a bottom-up versus a top-down theory of early phonological development by leveling the power of results from thousands of infants. We predicted that if infants can rely purely on auditory experience to develop their phonological categories, then vowel discrimination and word segmentation should develop in parallel, with the latter being potentially lagged compared to the former. However, if infants crucially rely on word form information to build their phonological categories, then development at the word level must precede the acquisition of native sound categories. Our results do not support the latter prediction. We discuss potential implications and limitations, most saliently that word forms are only one top-down level proposed to affect phonological development, with other proposals suggesting that top-down pressures emerge from lexical (i.e., word-meaning pairs) development. This investigation also highlights general procedures by which standardized meta-analyses may be reused to answer theoretical questions spanning across phenomena.

    Additional information

    Scripts and data
  • Black, A., & Bergmann, C. (2017). Quantifying infants' statistical word segmentation: A meta-analysis. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Meeting of the Cognitive Science Society (pp. 124-129). Austin, TX: Cognitive Science Society.

    Abstract

    Theories of language acquisition and perceptual learning increasingly rely on statistical learning mechanisms. The current meta-analysis aims to clarify the robustness of this capacity in infancy within the word segmentation literature. Our analysis reveals a significant, small effect size for conceptual replications of Saffran, Aslin, & Newport (1996), and a nonsignificant effect across all studies that incorporate transitional probabilities to segment words. In both conceptual replications and the broader literature, however, statistical learning is moderated by whether stimuli are naturally produced or synthesized. These findings invite deeper questions about the complex factors that influence statistical learning, and the role of statistical learning in language acquisition.
  • Bohnemeyer, J. (1997). Yucatec Mayan Lexicalization Patterns in Time and Space. In M. Biemans, & J. van de Weijer (Eds.), Proceedings of the CLS opening of the academic year '97-'98. Tilburg, The Netherlands: University Center for Language Studies.
  • Bosker, H. R., & Kösem, A. (2017). An entrained rhythm's frequency, not phase, influences temporal sampling of speech. In Proceedings of Interspeech 2017 (pp. 2416-2420). doi:10.21437/Interspeech.2017-73.

    Abstract

    Brain oscillations have been shown to track the slow amplitude fluctuations in speech during comprehension. Moreover, there is evidence that these stimulus-induced cortical rhythms may persist even after the driving stimulus has ceased. However, how exactly this neural entrainment shapes speech perception remains debated. This behavioral study investigated whether and how the frequency and phase of an entrained rhythm would influence the temporal sampling of subsequent speech. In two behavioral experiments, participants were presented with slow and fast isochronous tone sequences, followed by Dutch target words ambiguous between as /ɑs/ “ash” (with a short vowel) and aas /a:s/ “bait” (with a long vowel). Target words were presented at various phases of the entrained rhythm. Both experiments revealed effects of the frequency of the tone sequence on target word perception: fast sequences biased listeners to more long /a:s/ responses. However, no evidence for phase effects could be discerned. These findings show that an entrained rhythm’s frequency, but not phase, influences the temporal sampling of subsequent speech. These outcomes are compatible with theories suggesting that sensory timing is evaluated relative to entrained frequency. Furthermore, they suggest that phase tracking of (syllabic) rhythms by theta oscillations plays a limited role in speech parsing.
  • Bosker, H. R. (2017). The role of temporal amplitude modulations in the political arena: Hillary Clinton vs. Donald Trump. In Proceedings of Interspeech 2017 (pp. 2228-2232). doi:10.21437/Interspeech.2017-142.

    Abstract

    Speech is an acoustic signal with inherent amplitude modulations in the 1-9 Hz range. Recent models of speech perception propose that this rhythmic nature of speech is central to speech recognition. Moreover, rhythmic amplitude modulations have been shown to have beneficial effects on language processing and the subjective impression listeners have of the speaker. This study investigated the role of amplitude modulations in the political arena by comparing the speech produced by Hillary Clinton and Donald Trump in the three presidential debates of 2016. Inspection of the modulation spectra, revealing the spectral content of the two speakers’ amplitude envelopes after matching for overall intensity, showed considerably greater power in Clinton’s modulation spectra (compared to Trump’s) across the three debates, particularly in the 1-9 Hz range. The findings suggest that Clinton’s speech had a more pronounced temporal envelope with rhythmic amplitude modulations below 9 Hz, with a preference for modulations around 3 Hz. This may be taken as evidence for a more structured temporal organization of syllables in Clinton’s speech, potentially due to more frequent use of preplanned utterances. Outcomes are interpreted in light of the potential beneficial effects of a rhythmic temporal envelope on intelligibility and speaker perception.
  • Böttner, M. (1997). Visiting some relatives of Peirce's. In 3rd International Seminar on The use of Relational Methods in Computer Science.

    Abstract

    The notion of relational grammar is extented to ternary relations and illustrated by a fragment of English. Some of Peirce's terms for ternary relations are shown to be incorrect and corrected.
  • 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.
  • Burchfield, L. A., Luk, S.-.-H.-K., Antoniou, M., & Cutler, A. (2017). Lexically guided perceptual learning in Mandarin Chinese. In Proceedings of Interspeech 2017 (pp. 576-580). doi:10.21437/Interspeech.2017-618.

    Abstract

    Lexically guided perceptual learni ng refers to the use of lexical knowledge to retune sp eech categories and thereby adapt to a novel talker’s pronunciation. This adaptation has been extensively documented, but primarily for segmental-based learning in English and Dutch. In languages with lexical tone, such as Mandarin Chinese, tonal categories can also be retuned in this way, but segmental category retuning had not been studied. We report two experiment s in which Mandarin Chinese listeners were exposed to an ambiguous mixture of [f] and [s] in lexical contexts favoring an interpretation as either [f] or [s]. Listeners were subsequently more likely to identify sounds along a continuum between [f] and [s], and to interpret minimal word pairs, in a manner consistent with this exposure. Thus lexically guided perceptual learning of segmental categories had indeed taken place, consistent with suggestions that such learning may be a universally available adaptation process
  • Butterfield, S., & Cutler, A. (1988). Segmentation errors by human listeners: Evidence for a prosodic segmentation strategy. In W. Ainsworth, & J. Holmes (Eds.), Proceedings of SPEECH ’88: Seventh Symposium of the Federation of Acoustic Societies of Europe: Vol. 3 (pp. 827-833). Edinburgh: Institute of Acoustics.
  • 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.
  • Casillas, M., Bergelson, E., Warlaumont, A. S., Cristia, A., Soderstrom, M., VanDam, M., & Sloetjes, H. (2017). A New Workflow for Semi-automatized Annotations: Tests with Long-Form Naturalistic Recordings of Childrens Language Environments. In Proceedings of Interspeech 2017 (pp. 2098-2102). doi:10.21437/Interspeech.2017-1418.

    Abstract

    Interoperable annotation formats are fundamental to the utility, expansion, and sustainability of collective data repositories.In language development research, shared annotation schemes have been critical to facilitating the transition from raw acoustic data to searchable, structured corpora. Current schemes typically require comprehensive and manual annotation of utterance boundaries and orthographic speech content, with an additional, optional range of tags of interest. These schemes have been enormously successful for datasets on the scale of dozens of recording hours but are untenable for long-format recording corpora, which routinely contain hundreds to thousands of audio hours. Long-format corpora would benefit greatly from (semi-)automated analyses, both on the earliest steps of annotation—voice activity detection, utterance segmentation, and speaker diarization—as well as later steps—e.g., classification-based codes such as child-vs-adult-directed speech, and speech recognition to produce phonetic/orthographic representations. We present an annotation workflow specifically designed for long-format corpora which can be tailored by individual researchers and which interfaces with the current dominant scheme for short-format recordings. The workflow allows semi-automated annotation and analyses at higher linguistic levels. We give one example of how the workflow has been successfully implemented in a large cross-database project.
  • Casillas, M., Amatuni, A., Seidl, A., Soderstrom, M., Warlaumont, A., & Bergelson, E. (2017). What do Babies hear? Analyses of Child- and Adult-Directed Speech. In Proceedings of Interspeech 2017 (pp. 2093-2097). doi:10.21437/Interspeech.2017-1409.

    Abstract

    Child-directed speech is argued to facilitate language development, and is found cross-linguistically and cross-culturally to varying degrees. However, previous research has generally focused on short samples of child-caregiver interaction, often in the lab or with experimenters present. We test the generalizability of this phenomenon with an initial descriptive analysis of the speech heard by young children in a large, unique collection of naturalistic, daylong home recordings. Trained annotators coded automatically-detected adult speech 'utterances' from 61 homes across 4 North American cities, gathered from children (age 2-24 months) wearing audio recorders during a typical day. Coders marked the speaker gender (male/female) and intended addressee (child/adult), yielding 10,886 addressee and gender tags from 2,523 minutes of audio (cf. HB-CHAAC Interspeech ComParE challenge; Schuller et al., in press). Automated speaker-diarization (LENA) incorrectly gender-tagged 30% of male adult utterances, compared to manually-coded consensus. Furthermore, we find effects of SES and gender on child-directed and overall speech, increasing child-directed speech with child age, and interactions of speaker gender, child gender, and child age: female caretakers increased their child-directed speech more with age than male caretakers did, but only for male infants. Implications for language acquisition and existing classification algorithms are discussed.
  • Crago, M. B., & Allen, S. E. M. (1997). Linguistic and cultural aspects of simplicity and complexity in Inuktitut child directed speech. In E. Hughes, M. Hughes, & A. Greenhill (Eds.), Proceedings of the 21st annual Boston University Conference on Language Development (pp. 91-102).
  • 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.
  • Ip, M. H. K., & Cutler, A. (2018). Asymmetric efficiency of juncture perception in L1 and L2. In K. Klessa, J. Bachan, A. Wagner, M. Karpiński, & D. Śledziński (Eds.), Proceedings of Speech Prosody 2018 (pp. 289-296). Baixas, France: ISCA. doi:10.21437/SpeechProsody.2018-59.

    Abstract

    In two experiments, Mandarin listeners resolved potential syntactic ambiguities in spoken utterances in (a) their native language (L1) and (b) English which they had learned as a second language (L2). A new disambiguation task was used, requiring speeded responses to select the correct meaning for structurally ambiguous sentences. Importantly, the ambiguities used in the study are identical in Mandarin and in English, and production data show that prosodic disambiguation of this type of ambiguity is also realised very similarly in the two languages. The perceptual results here showed however that listeners’ response patterns differed for L1 and L2, although there was a significant increase in similarity between the two response patterns with increasing exposure to the L2. Thus identical ambiguity and comparable disambiguation patterns in L1 and L2 do not lead to immediate application of the appropriate L1 listening strategy to L2; instead, it appears that such a strategy may have to be learned anew for the L2.
  • Cutler, A. (2017). Converging evidence for abstract phonological knowledge in speech 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. 1447-1448). Austin, TX: Cognitive Science Society.

    Abstract

    The perceptual processing of speech is a constant interplay of multiple competing albeit convergent processes: acoustic input vs. higher-level representations, universal mechanisms vs. language-specific, veridical traces of speech experience vs. construction and activation of abstract representations. The present summary concerns the third of these issues. The ability to generalise across experience and to deal with resulting abstractions is the hallmark of human cognition, visible even in early infancy. In speech processing, abstract representations play a necessary role in both production and perception. New sorts of evidence are now informing our understanding of the breadth of this role.
  • 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.
  • Ip, M. H. K., & Cutler, A. (2017). Intonation facilitates prediction of focus even in the presence of lexical tones. In Proceedings of Interspeech 2017 (pp. 1218-1222). doi:10.21437/Interspeech.2017-264.

    Abstract

    In English and Dutch, listeners entrain to prosodic contours to predict where focus will fall in an utterance. However, is this strategy universally available, even in languages with different phonological systems? In a phoneme detection experiment, we examined whether prosodic entrainment is also found in Mandarin Chinese, a tone language, where in principle the use of pitch for lexical identity may take precedence over the use of pitch cues to salience. Consistent with the results from Germanic languages, response times were facilitated when preceding intonation predicted accent on the target-bearing word. Acoustic analyses revealed greater F0 range in the preceding intonation of the predicted-accent sentences. These findings have implications for how universal and language-specific mechanisms interact in the processing of salience.
  • 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. (1980). Productivity in word formation. In J. Kreiman, & A. E. Ojeda (Eds.), Papers from the Sixteenth Regional Meeting, Chicago Linguistic Society (pp. 45-51). Chicago, Ill.: CLS.
  • Cutler, A., & Butterfield, S. (1986). The perceptual integrity of initial consonant clusters. In R. Lawrence (Ed.), Speech and Hearing: Proceedings of the Institute of Acoustics (pp. 31-36). Edinburgh: Institute of Acoustics.
  • Delgado, T., Ravignani, A., Verhoef, T., Thompson, B., Grossi, T., & Kirby, S. (2018). Cultural transmission of melodic and rhythmic universals: Four experiments and a model. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 89-91). Toruń, Poland: NCU Press. doi:10.12775/3991-1.019.
  • Doumas, L. A. A., Hamer, A., Puebla, G., & Martin, A. E. (2017). A theory of the detection and learning of structured representations of similarity and relative magnitude. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (CogSci 2017) (pp. 1955-1960). Austin, TX: Cognitive Science Society.

    Abstract

    Responding to similarity, difference, and relative magnitude (SDM) is ubiquitous in the animal kingdom. However, humans seem unique in the ability to represent relative magnitude (‘more’/‘less’) and similarity (‘same’/‘different’) as abstract relations that take arguments (e.g., greater-than (x,y)). While many models use structured relational representations of magnitude and similarity, little progress has been made on how these representations arise. Models that developuse these representations assume access to computations of similarity and magnitude a priori, either encoded as features or as output of evaluation operators. We detail a mechanism for producing invariant responses to “same”, “different”, “more”, and “less” which can be exploited to compute similarity and magnitude as an evaluation operator. Using DORA (Doumas, Hummel, & Sandhofer, 2008), these invariant responses can serve be used to learn structured relational representations of relative magnitude and similarity from pixel images of simple shapes
  • 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.
  • Edmiston, P., Perlman, M., & Lupyan, G. (2017). Creating words from iterated vocal imitation. In G. Gunzelman, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (CogSci 2017) (pp. 331-336). Austin, TX: Cognitive Science Society.

    Abstract

    We report the results of a large-scale (N=1571) experiment to investigate whether spoken words can emerge from the process of repeated imitation. Participants played a version of the children’s game “Telephone”. The first generation was asked to imitate recognizable environmental sounds (e.g., glass breaking, water splashing); subsequent generations imitated the imitators for a total of 8 generations. We then examined whether the vocal imitations became more stable and word-like, retained a resemblance to the original sound, and became more suitable as learned category labels. The results showed (1) the imitations became progressively more word-like, (2) even after 8 generations, they could be matched above chance to the environmental sound that motivated them, and (3) imitations from later generations were more effective as learned category labels. These results show how repeated imitation can create progressively more word-like forms while retaining a semblance of iconicity.
  • 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.
  • Franken, M. K., Eisner, F., Schoffelen, J.-M., Acheson, D. J., Hagoort, P., & McQueen, J. M. (2017). Audiovisual recalibration of vowel categories. In Proceedings of Interspeech 2017 (pp. 655-658). doi:10.21437/Interspeech.2017-122.

    Abstract

    One of the most daunting tasks of a listener is to map a
    continuous auditory stream onto known speech sound
    categories and lexical items. A major issue with this mapping
    problem is the variability in the acoustic realizations of sound
    categories, both within and across speakers. Past research has
    suggested listeners may use visual information (e.g., lipreading)
    to calibrate these speech categories to the current
    speaker. Previous studies have focused on audiovisual
    recalibration of consonant categories. The present study
    explores whether vowel categorization, which is known to show
    less sharply defined category boundaries, also benefit from
    visual cues.
    Participants were exposed to videos of a speaker
    pronouncing one out of two vowels, paired with audio that was
    ambiguous between the two vowels. After exposure, it was
    found that participants had recalibrated their vowel categories.
    In addition, individual variability in audiovisual recalibration is
    discussed. It is suggested that listeners’ category sharpness may
    be related to the weight they assign to visual information in
    audiovisual speech perception. Specifically, listeners with less
    sharp categories assign more weight to visual information
    during audiovisual speech recognition.
  • Fusaroli, R., Tylén, K., Garly, K., Steensig, J., Christiansen, M. H., & Dingemanse, M. (2017). Measures and mechanisms of common ground: Backchannels, conversational repair, and interactive alignment in free and task-oriented social interactions. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (CogSci 2017) (pp. 2055-2060). Austin, TX: Cognitive Science Society.

    Abstract

    A crucial aspect of everyday conversational interactions is our ability to establish and maintain common ground. Understanding the relevant mechanisms involved in such social coordination remains an important challenge for cognitive science. While common ground is often discussed in very general terms, different contexts of interaction are likely to afford different coordination mechanisms. In this paper, we investigate the presence and relation of three mechanisms of social coordination – backchannels, interactive alignment and conversational repair – across free and task-oriented conversations. We find significant differences: task-oriented conversations involve higher presence of repair – restricted offers in particular – and backchannel, as well as a reduced level of lexical and syntactic alignment. We find that restricted repair is associated with lexical alignment and open repair with backchannels. Our findings highlight the need to explicitly assess several mechanisms at once and to investigate diverse activities to understand their role and relations.
  • 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.
  • Galke, L., Mai, F., Schelten, A., Brunch, D., & Scherp, A. (2017). Using titles vs. full-text as source for automated semantic document annotation. In O. Corcho, K. Janowicz, G. Rizz, I. Tiddi, & D. Garijo (Eds.), Proceedings of the 9th International Conference on Knowledge Capture (K-CAP 2017). New York: ACM.

    Abstract

    We conduct the first systematic comparison of automated semantic
    annotation based on either the full-text or only on the title metadata
    of documents. Apart from the prominent text classification baselines
    kNN and SVM, we also compare recent techniques of Learning
    to Rank and neural networks and revisit the traditional methods
    logistic regression, Rocchio, and Naive Bayes. Across three of our
    four datasets, the performance of the classifications using only titles
    reaches over 90% of the quality compared to the performance when
    using the full-text.
  • Galke, L., Saleh, A., & Scherp, A. (2017). Word embeddings for practical information retrieval. In M. Eibl, & M. Gaedke (Eds.), INFORMATIK 2017 (pp. 2155-2167). Bonn: Gesellschaft für Informatik. doi:10.18420/in2017_215.

    Abstract

    We assess the suitability of word embeddings for practical information retrieval scenarios. Thus, we assume that users issue ad-hoc short queries where we return the first twenty retrieved documents after applying a boolean matching operation between the query and the documents. We compare the performance of several techniques that leverage word embeddings in the retrieval models to compute the similarity between the query and the documents, namely word centroid similarity, paragraph vectors, Word Mover’s distance, as well as our novel inverse document frequency (IDF) re-weighted word centroid similarity. We evaluate the performance using the ranking metrics mean average precision, mean reciprocal rank, and normalized discounted cumulative gain. Additionally, we inspect the retrieval models’ sensitivity to document length by using either only the title or the full-text of the documents for the retrieval task. We conclude that word centroid similarity is the best competitor to state-of-the-art retrieval models. It can be further improved by re-weighting the word frequencies with IDF before aggregating the respective word vectors of the embedding. The proposed cosine similarity of IDF re-weighted word vectors is competitive to the TF-IDF baseline and even outperforms it in case of the news domain with a relative percentage of 15%.
  • Hopman, E., Thompson, B., Austerweil, J., & Lupyan, G. (2018). Predictors of L2 word learning accuracy: A big data investigation. In C. Kalish, M. Rau, J. Zhu, & T. T. Rogers (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (CogSci 2018) (pp. 513-518). Austin, TX: Cognitive Science Society.

    Abstract

    What makes some words harder to learn than others in a second language? Although some robust factors have been identified based on small scale experimental studies, many relevant factors are difficult to study in such experiments due to the amount of data necessary to test them. Here, we investigate what factors affect the ease of learning of a word in a second language using a large data set of users learning English as a second language through the Duolingo mobile app. In a regression analysis, we test and confirm the well-studied effect of cognate status on word learning accuracy. Furthermore, we find significant effects for both cross-linguistic semantic alignment and English semantic density, two novel predictors derived from large scale distributional models of lexical semantics. Finally, we provide data on several other psycholinguistically plausible word level predictors. We conclude with a discussion of the limits, benefits and future research potential of using big data for investigating second language learning.
  • Huettig, F., Kolinsky, R., & Lachmann, T. (Eds.). (2018). The effects of literacy on cognition and brain functioning [Special Issue]. Language, Cognition and Neuroscience, 33(3).
  • Isbilen, E., Frost, R. L. A., Monaghan, P., & Christiansen, M. (2018). Bridging artificial and natural language learning: Comparing processing- and reflection-based measures of learning. In C. Kalish, M. Rau, J. Zhu, & T. T. Rogers (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (CogSci 2018) (pp. 1856-1861). Austin, TX: Cognitive Science Society.

    Abstract

    A common assumption in the cognitive sciences is that artificial and natural language learning rely on shared mechanisms. However, attempts to bridge the two have yielded ambiguous results. We suggest that an empirical disconnect between the computations employed during learning and the methods employed at test may explain these mixed results. Further, we propose statistically-based chunking as a potential computational link between artificial and natural language learning. We compare the acquisition of non-adjacent dependencies to that of natural language structure using two types of tasks: reflection-based 2AFC measures, and processing-based recall measures, the latter being more computationally analogous to the processes used during language acquisition. Our results demonstrate that task-type significantly influences the correlations observed between artificial and natural language acquisition, with reflection-based and processing-based measures correlating within – but not across – task-type. These findings have fundamental implications for artificial-to-natural language comparisons, both methodologically and theoretically.
  • Isbilen, E. S., McCauley, S. M., Kidd, E., & Christiansen, M. H. (2017). Testing statistical learning implicitly: A novel chunk-based measure of statistical learning. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (CogSci 2017) (pp. 564-569). Austin, TX: Cognitive Science Society.

    Abstract

    Attempts to connect individual differences in statistical learning with broader aspects of cognition have received considerable attention, but have yielded mixed results. A possible explanation is that statistical learning is typically tested using the two-alternative forced choice (2AFC) task. As a meta-cognitive task relying on explicit familiarity judgments, 2AFC may not accurately capture implicitly formed statistical computations. In this paper, we adapt the classic serial-recall memory paradigm to implicitly test statistical learning in a statistically-induced chunking recall (SICR) task. We hypothesized that artificial language exposure would lead subjects to chunk recurring statistical patterns, facilitating recall of words from the input. Experiment 1 demonstrates that SICR offers more fine-grained insights into individual differences in statistical learning than 2AFC. Experiment 2 shows that SICR has higher test-retest reliability than that reported for 2AFC. Thus, SICR offers a more sensitive measure of individual differences, suggesting that basic chunking abilities may explain statistical learning.
  • 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.
  • 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
  • Kapatsinski, V., & Harmon, Z. (2017). A Hebbian account of entrenchment and (over)-extension in language learning. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Meeting of the Cognitive Science Society (CogSci 2017) (pp. 2366-2371). Austin, TX: Cognitive Science Society.

    Abstract

    In production, frequently used words are preferentially extended to new, though related meanings. In comprehension, frequent exposure to a word instead makes the learner confident that all of the word’s legitimate uses have been experienced, resulting in an entrenched form-meaning mapping between the word and its experienced meaning(s). This results in a perception-production dissociation, where the forms speakers are most likely to map onto a novel meaning are precisely the forms that they believe can never be used that way. At first glance, this result challenges the idea of bidirectional form-meaning mappings, assumed by all current approaches to linguistic theory. In this paper, we show that bidirectional form-meaning mappings are not in fact challenged by this production-perception dissociation. We show that the production-perception dissociation is expected even if learners of the lexicon acquire simple symmetrical form-meaning associations through simple Hebbian learning.
  • Karadöller, D. Z., Sumer, B., & Ozyurek, A. (2017). Effects of delayed language exposure on spatial language acquisition by signing children and adults. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (CogSci 2017) (pp. 2372-2376). Austin, TX: Cognitive Science Society.

    Abstract

    Deaf children born to hearing parents are exposed to language input quite late, which has long-lasting effects on language production. Previous studies with deaf individuals mostly focused on linguistic expressions of motion events, which have several event components. We do not know if similar effects emerge in simple events such as descriptions of spatial configurations of objects. Moreover, previous data mainly come from late adult signers. There is not much known about language development of late signing children soon after learning sign language. We compared simple event descriptions of late signers of Turkish Sign Language (adults, children) to age-matched native signers. Our results indicate that while late signers in both age groups are native-like in frequency of expressing a relational encoding, they lag behind native signers in using morphologically complex linguistic forms compared to other simple forms. Late signing children perform similar to adults and thus showed no development over time.
  • Kember, H., Grohe, A.-.-K., Zahner, K., Braun, B., Weber, A., & Cutler, A. (2017). Similar prosodic structure perceived differently in German and English. In Proceedings of Interspeech 2017 (pp. 1388-1392). doi:10.21437/Interspeech.2017-544.

    Abstract

    English and German have similar prosody, but their speakers realize some pitch falls (not rises) in subtly different ways. We here test for asymmetry in perception. An ABX discrimination task requiring F0 slope or duration judgements on isolated vowels revealed no cross-language difference in duration or F0 fall discrimination, but discrimination of rises (realized similarly in each language) was less accurate for English than for German listeners. This unexpected finding may reflect greater sensitivity to rising patterns by German listeners, or reduced sensitivity by English listeners as a result of extensive exposure to phrase-final rises (“uptalk”) in their language
  • Kempen, G. (1988). De netwerker: Spin in het web of rat in een doolhof? In SURF in theorie en praktijk: Van personal tot supercomputer (pp. 59-61). Amsterdam: Elsevier Science Publishers.
  • Kempen, G. (1997). De ontdubbelde taalgebruiker: Maken taalproductie en taalperceptie gebruik van één en dezelfde syntactische processor? [Abstract]. In 6e Winter Congres NvP. Programma and abstracts (pp. 31-32). Nederlandse Vereniging voor Psychonomie.
  • Kempen, G., Kooij, A., & Van Leeuwen, T. (1997). Do skilled readers exploit inflectional spelling cues that do not mirror pronunciation? An eye movement study of morpho-syntactic parsing in Dutch. In Abstracts of the Orthography Workshop "What spelling changes". Nijmegen: Max Planck Institute for Psycholinguistics.
  • Klein, W. (Ed.). (1980). Argumentation [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (38/39).
  • Klein, W. (Ed.). (1997). Technologischer Wandel in den Philologien [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (106).
  • Klein, W. (Ed.). (1988). Sprache Kranker [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (69).
  • Klein, W. (Ed.). (1986). Sprachverfall [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (62).
  • Koster, M., & Cutler, A. (1997). Segmental and suprasegmental contributions to spoken-word recognition in Dutch. In Proceedings of EUROSPEECH 97 (pp. 2167-2170). Grenoble, France: ESCA.

    Abstract

    Words can be distinguished by segmental differences or by suprasegmental differences or both. Studies from English suggest that suprasegmentals play little role in human spoken-word recognition; English stress, however, is nearly always unambiguously coded in segmental structure (vowel quality); this relationship is less close in Dutch. The present study directly compared the effects of segmental and suprasegmental mispronunciation on word recognition in Dutch. There was a strong effect of suprasegmental mispronunciation, suggesting that Dutch listeners do exploit suprasegmental information in word recognition. Previous findings indicating the effects of mis-stressing for Dutch differ with stress position were replicated only when segmental change was involved, suggesting that this is an effect of segmental rather than suprasegmental processing.
  • 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.
  • Lee, R., Chambers, C. G., Huettig, F., & Ganea, P. A. (2017). Children’s semantic and world knowledge overrides fictional information during anticipatory linguistic processing. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Meeting of the Cognitive Science Society (CogSci 2017) (pp. 730-735). Austin, TX: Cognitive Science Society.

    Abstract

    Using real-time eye-movement measures, we asked how a fantastical discourse context competes with stored representations of semantic and world knowledge to influence children's and adults' moment-by-moment interpretation of a story. Seven-year- olds were less effective at bypassing stored semantic and world knowledge during real-time interpretation than adults. Nevertheless, an effect of discourse context on comprehension was still apparent.
  • 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.
  • Little, H., Perlman, M., & Eryilmaz, K. (2017). Repeated interactions can lead to more iconic signals. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (CogSci 2017) (pp. 760-765). Austin, TX: Cognitive Science Society.

    Abstract

    Previous research has shown that repeated interactions can cause iconicity in signals to reduce. However, data from several recent studies has shown the opposite trend: an increase in iconicity as the result of repeated interactions. Here, we discuss whether signals may become less or more iconic as a result of the modality used to produce them. We review several recent experimental results before presenting new data from multi-modal signals, where visual input creates audio feedback. Our results show that the growth in iconicity present in the audio information may come at a cost to iconicity in the visual information. Our results have implications for how we think about and measure iconicity in artificial signalling experiments. Further, we discuss how iconicity in real world speech may stem from auditory, kinetic or visual information, but iconicity in these different modalities may conflict.
  • Little, H. (Ed.). (2017). Special Issue on the Emergence of Sound Systems [Special Issue]. The Journal of Language Evolution, 2(1).
  • Lopopolo, A., Frank, S. L., Van den Bosch, A., Nijhof, A., & Willems, R. M. (2018). The Narrative Brain Dataset (NBD), an fMRI dataset for the study of natural language processing in the brain. In B. Devereux, E. Shutova, & C.-R. Huang (Eds.), Proceedings of LREC 2018 Workshop "Linguistic and Neuro-Cognitive Resources (LiNCR) (pp. 8-11). Paris: LREC.

    Abstract

    We present the Narrative Brain Dataset, an fMRI dataset that was collected during spoken presentation of short excerpts of three
    stories in Dutch. Together with the brain imaging data, the dataset contains the written versions of the stimulation texts. The texts are
    accompanied with stochastic (perplexity and entropy) and semantic computational linguistic measures. The richness and unconstrained
    nature of the data allows the study of language processing in the brain in a more naturalistic setting than is common for fMRI studies.
    We hope that by making NBD available we serve the double purpose of providing useful neural data to researchers interested in natural
    language processing in the brain and to further stimulate data sharing in the field of neuroscience of language.
  • Lupyan, G., Wendorf, A., Berscia, L. M., & Paul, J. (2018). Core knowledge or language-augmented cognition? The case of geometric reasoning. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 252-254). Toruń, Poland: NCU Press. doi:10.12775/3991-1.062.
  • Mai, F., Galke, L., & Scherp, A. (2018). Using deep learning for title-based semantic subject indexing to reach competitive performance to full-text. In J. Chen, M. A. Gonçalves, J. M. Allen, E. A. Fox, M.-Y. Kan, & V. Petras (Eds.), JCDL '18: Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries (pp. 169-178). New York: ACM.

    Abstract

    For (semi-)automated subject indexing systems in digital libraries, it is often more practical to use metadata such as the title of a publication instead of the full-text or the abstract. Therefore, it is desirable to have good text mining and text classification algorithms that operate well already on the title of a publication. So far, the classification performance on titles is not competitive with the performance on the full-texts if the same number of training samples is used for training. However, it is much easier to obtain title data in large quantities and to use it for training than full-text data. In this paper, we investigate the question how models obtained from training on increasing amounts of title training data compare to models from training on a constant number of full-texts. We evaluate this question on a large-scale dataset from the medical domain (PubMed) and from economics (EconBiz). In these datasets, the titles and annotations of millions of publications are available, and they outnumber the available full-texts by a factor of 20 and 15, respectively. To exploit these large amounts of data to their full potential, we develop three strong deep learning classifiers and evaluate their performance on the two datasets. The results are promising. On the EconBiz dataset, all three classifiers outperform their full-text counterparts by a large margin. The best title-based classifier outperforms the best full-text method by 9.4%. On the PubMed dataset, the best title-based method almost reaches the performance of the best full-text classifier, with a difference of only 2.9%.
  • Maslowski, M., Meyer, A. S., & Bosker, H. R. (2017). Whether long-term tracking of speech rate affects perception depends on who is talking. In Proceedings of Interspeech 2017 (pp. 586-590). doi:10.21437/Interspeech.2017-1517.

    Abstract

    Speech rate is known to modulate perception of temporally ambiguous speech sounds. For instance, a vowel may be perceived as short when the immediate speech context is slow, but as long when the context is fast. Yet, effects of long-term tracking of speech rate are largely unexplored. Two experiments tested whether long-term tracking of rate influences perception of the temporal Dutch vowel contrast /ɑ/-/a:/. In Experiment 1, one low-rate group listened to 'neutral' rate speech from talker A and to slow speech from talker B. Another high-rate group was exposed to the same neutral speech from A, but to fast speech from B. Between-group comparison of the 'neutral' trials revealed that the low-rate group reported a higher proportion of /a:/ in A's 'neutral' speech, indicating that A sounded faster when B was slow. Experiment 2 tested whether one's own speech rate also contributes to effects of long-term tracking of rate. Here, talker B's speech was replaced by playback of participants' own fast or slow speech. No evidence was found that one's own voice affected perception of talker A in larger speech contexts. These results carry implications for our understanding of the mechanisms involved in rate-dependent speech perception and of dialogue.
  • Merkx, D., & Scharenborg, O. (2018). Articulatory feature classification using convolutional neural networks. In Proceedings of Interspeech 2018 (pp. 2142-2146). doi:10.21437/Interspeech.2018-2275.

    Abstract

    The ultimate goal of our research is to improve an existing speech-based computational model of human speech recognition on the task of simulating the role of fine-grained phonetic information in human speech processing. As part of this work we are investigating articulatory feature classifiers that are able to create reliable and accurate transcriptions of the articulatory behaviour encoded in the acoustic speech signal. Articulatory feature (AF) modelling of speech has received a considerable amount of attention in automatic speech recognition research. Different approaches have been used to build AF classifiers, most notably multi-layer perceptrons. Recently, deep neural networks have been applied to the task of AF classification. This paper aims to improve AF classification by investigating two different approaches: 1) investigating the usefulness of a deep Convolutional neural network (CNN) for AF classification; 2) integrating the Mel filtering operation into the CNN architecture. The results showed a remarkable improvement in classification accuracy of the CNNs over state-of-the-art AF classification results for Dutch, most notably in the minority classes. Integrating the Mel filtering operation into the CNN architecture did not further improve classification performance.
  • Micklos, A., Macuch Silva, V., & Fay, N. (2018). The prevalence of repair in studies of language evolution. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 316-318). Toruń, Poland: NCU Press. doi:10.12775/3991-1.075.
  • Monaghan, P., Brand, J., Frost, R. L. A., & Taylor, G. (2017). Multiple variable cues in the environment promote accurate and robust word learning. In G. Gunzelman, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (CogSci 2017) (pp. 817-822). Retrieved from https://mindmodeling.org/cogsci2017/papers/0164/index.html.

    Abstract

    Learning how words refer to aspects of the environment is a complex task, but one that is supported by numerous cues within the environment which constrain the possibilities for matching words to their intended referents. In this paper we tested the predictions of a computational model of multiple cue integration for word learning, that predicted variation in the presence of cues provides an optimal learning situation. In a cross-situational learning task with adult participants, we varied the reliability of presence of distributional, prosodic, and gestural cues. We found that the best learning occurred when cues were often present, but not always. The effect of variability increased the salience of individual cues for the learner, but resulted in robust learning that was not vulnerable to individual cues’ presence or absence. Thus, variability of multiple cues in the language-learning environment provided the optimal circumstances for word learning.
  • Mulder, K., Ten Bosch, L., & Boves, L. (2018). Analyzing EEG Signals in Auditory Speech Comprehension Using Temporal Response Functions and Generalized Additive Models. In Proceedings of Interspeech 2018 (pp. 1452-1456). doi:10.21437/Interspeech.2018-1676.

    Abstract

    Analyzing EEG signals recorded while participants are listening to continuous speech with the purpose of testing linguistic hypotheses is complicated by the fact that the signals simultaneously reflect exogenous acoustic excitation and endogenous linguistic processing. This makes it difficult to trace subtle differences that occur in mid-sentence position. We apply an analysis based on multivariate temporal response functions to uncover subtle mid-sentence effects. This approach is based on a per-stimulus estimate of the response of the neural system to speech input. Analyzing EEG signals predicted on the basis of the response functions might then bring to light conditionspecific differences in the filtered signals. We validate this approach by means of an analysis of EEG signals recorded with isolated word stimuli. Then, we apply the validated method to the analysis of the responses to the same words in the middle of meaningful sentences.
  • Ortega, G., Schiefner, A., & Ozyurek, A. (2017). Speakers’ gestures predict the meaning and perception of iconicity in signs. In G. Gunzelmann, A. Howe, & T. Tenbrink (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (CogSci 2017) (pp. 889-894). Austin, TX: Cognitive Science Society.

    Abstract

    Sign languages stand out in that there is high prevalence of
    conventionalised linguistic forms that map directly to their
    referent (i.e., iconic). Hearing adults show low performance
    when asked to guess the meaning of iconic signs suggesting
    that their iconic features are largely inaccessible to them.
    However, it has not been investigated whether speakers’
    gestures, which also share the property of iconicity, may
    assist non-signers in guessing the meaning of signs. Results
    from a pantomime generation task (Study 1) show that
    speakers’ gestures exhibit a high degree of systematicity, and
    share different degrees of form overlap with signs (full,
    partial, and no overlap). Study 2 shows that signs with full
    and partial overlap are more accurately guessed and are
    assigned higher iconicity ratings than signs with no overlap.
    Deaf and hearing adults converge in their iconic depictions
    for some concepts due to the shared conceptual knowledge
    and manual-visual modality.
  • Pallier, C., Cutler, A., & Sebastian-Galles, N. (1997). Prosodic structure and phonetic processing: A cross-linguistic study. In Proceedings of EUROSPEECH 97 (pp. 2131-2134). Grenoble, France: ESCA.

    Abstract

    Dutch and Spanish differ in how predictable the stress pattern is as a function of the segmental content: it is correlated with syllable weight in Dutch but not in Spanish. In the present study, two experiments were run to compare the abilities of Dutch and Spanish speakers to separately process segmental and stress information. It was predicted that the Spanish speakers would have more difficulty focusing on the segments and ignoring the stress pattern than the Dutch speakers. The task was a speeded classification task on CVCV syllables, with blocks of trials in which the stress pattern could vary versus blocks in which it was fixed. First, we found interference due to stress variability in both languages, suggesting that the processing of segmental information cannot be performed independently of stress. Second, the effect was larger for Spanish than for Dutch, suggesting that that the degree of interference from stress variation may be partially mitigated by the predictability of stress placement in the language.
  • Perlman, M., Fusaroli, R., Fein, D., & Naigles, L. (2017). The use of iconic words in early child-parent interactions. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (CogSci 2017) (pp. 913-918). Austin, TX: Cognitive Science Society.

    Abstract

    This paper examines the use of iconic words in early conversations between children and caregivers. The longitudinal data include a span of six observations of 35 children-parent dyads in the same semi-structured activity. Our findings show that children’s speech initially has a high proportion of iconic words, and over time, these words become diluted by an increase of arbitrary words. Parents’ speech is also initially high in iconic words, with a decrease in the proportion of iconic words over time – in this case driven by the use of fewer iconic words. The level and development of iconicity are related to individual differences in the children’s cognitive skills. Our findings fit with the hypothesis that iconicity facilitates early word learning and may play an important role in learning to produce new words.
  • Popov, V., Ostarek, M., & Tenison, C. (2017). Inferential Pitfalls in Decoding Neural Representations. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (CogSci 2017) (pp. 961-966). Austin, TX: Cognitive Science Society.

    Abstract

    A key challenge for cognitive neuroscience is to decipher the representational schemes of the brain. A recent class of decoding algorithms for fMRI data, stimulus-feature-based encoding models, is becoming increasingly popular for inferring the dimensions of neural representational spaces from stimulus-feature spaces. We argue that such inferences are not always valid, because decoding can occur even if the neural representational space and the stimulus-feature space use different representational schemes. This can happen when there is a systematic mapping between them. In a simulation, we successfully decoded the binary representation of numbers from their decimal features. Since binary and decimal number systems use different representations, we cannot conclude that the binary representation encodes decimal features. The same argument applies to the decoding of neural patterns from stimulus-feature spaces and we urge caution in inferring the nature of the neural code from such methods. We discuss ways to overcome these inferential limitations.
  • Pouw, W., Aslanidou, A., Kamermans, K. L., & Paas, F. (2017). Is ambiguity detection in haptic imagery possible? Evidence for Enactive imaginings. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (CogSci 2017) (pp. 2925-2930). Austin, TX: Cognitive Science Society.

    Abstract

    A classic discussion about visual imagery is whether it affords reinterpretation, like discovering two interpretations in the duck/rabbit illustration. Recent findings converge on reinterpretation being possible in visual imagery, suggesting functional equivalence with pictorial representations. However, it is unclear whether such reinterpretations are necessarily a visual-pictorial achievement. To assess this, 68 participants were briefly presented 2-d ambiguous figures. One figure was presented visually, the other via manual touch alone. Afterwards participants mentally rotated the memorized figures as to discover a novel interpretation. A portion (20.6%) of the participants detected a novel interpretation in visual imagery, replicating previous research. Strikingly, 23.6% of participants were able to reinterpret figures they had only felt. That reinterpretation truly involved haptic processes was further supported, as some participants performed co-thought gestures on an imagined figure during retrieval. These results are promising for further development of an Enactivist approach to imagination.
  • Räsänen, O., Seshadri, S., & Casillas, M. (2018). Comparison of syllabification algorithms and training strategies for robust word count estimation across different languages and recording conditions. In Proceedings of Interspeech 2018 (pp. 1200-1204). doi:10.21437/Interspeech.2018-1047.

    Abstract

    Word count estimation (WCE) from audio recordings has a number of applications, including quantifying the amount of speech that language-learning infants hear in their natural environments, as captured by daylong recordings made with devices worn by infants. To be applicable in a wide range of scenarios and also low-resource domains, WCE tools should be extremely robust against varying signal conditions and require minimal access to labeled training data in the target domain. For this purpose, earlier work has used automatic syllabification of speech, followed by a least-squares-mapping of syllables to word counts. This paper compares a number of previously proposed syllabifiers in the WCE task, including a supervised bi-directional long short-term memory (BLSTM) network that is trained on a language for which high quality syllable annotations are available (a “high resource language”), and reports how the alternative methods compare on different languages and signal conditions. We also explore additive noise and varying-channel data augmentation strategies for BLSTM training, and show how they improve performance in both matching and mismatching languages. Intriguingly, we also find that even though the BLSTM works on languages beyond its training data, the unsupervised algorithms can still outperform it in challenging signal conditions on novel languages.
  • Ravignani, A., Garcia, M., Gross, S., de Reus, K., Hoeksema, N., Rubio-Garcia, A., & de Boer, B. (2018). Pinnipeds have something to say about speech and rhythm. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 399-401). Toruń, Poland: NCU Press. doi:10.12775/3991-1.095.
  • Raviv, L., Meyer, A. S., & Lev-Ari, S. (2018). The role of community size in the emergence of linguistic structure. 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. 402-404). Toruń, Poland: NCU Press. doi:10.12775/3991-1.096.
  • Rubio-Fernández, P., & Jara-Ettinger, J. (2018). Joint inferences of speakers’ beliefs and referents based on how they speak. 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. 991-996). Austin, TX: Cognitive Science Society.

    Abstract

    For almost two decades, the poor performance observed with the so-called Director task has been interpreted as evidence of limited use of Theory of Mind in communication. Here we propose a probabilistic model of common ground in referential communication that derives three inferences from an utterance: what the speaker is talking about in a visual context, what she knows about the context, and what referential expressions she prefers. We tested our model by comparing its inferences with those made by human participants and found that it closely mirrors their judgments, whereas an alternative model compromising the hearer’s expectations of cooperativeness and efficiency reveals a worse fit to the human data. Rather than assuming that common ground is fixed in a given exchange and may or may not constrain reference resolution, we show how common ground can be inferred as part of the process of reference assignment.
  • Saleh, A., Beck, T., Galke, L., & Scherp, A. (2018). Performance comparison of ad-hoc retrieval models over full-text vs. titles of documents. In M. Dobreva, A. Hinze, & M. Žumer (Eds.), Maturity and Innovation in Digital Libraries: 20th International Conference on Asia-Pacific Digital Libraries, ICADL 2018, Hamilton, New Zealand, November 19-22, 2018, Proceedings (pp. 290-303). Cham, Switzerland: Springer.

    Abstract

    While there are many studies on information retrieval models using full-text, there are presently no comparison studies of full-text retrieval vs. retrieval only over the titles of documents. On the one hand, the full-text of documents like scientific papers is not always available due to, e.g., copyright policies of academic publishers. On the other hand, conducting a search based on titles alone has strong limitations. Titles are short and therefore may not contain enough information to yield satisfactory search results. In this paper, we compare different retrieval models regarding their search performance on the full-text vs. only titles of documents. We use different datasets, including the three digital library datasets: EconBiz, IREON, and PubMed. The results show that it is possible to build effective title-based retrieval models that provide competitive results comparable to full-text retrieval. The difference between the average evaluation results of the best title-based retrieval models is only 3% less than those of the best full-text-based retrieval models.
  • Scharenborg, O., & Merkx, D. (2018). The role of articulatory feature representation quality in a computational model of human spoken-word recognition. In Proceedings of the Machine Learning in Speech and Language Processing Workshop (MLSLP 2018).

    Abstract

    Fine-Tracker is a speech-based model of human speech
    recognition. While previous work has shown that Fine-Tracker
    is successful at modelling aspects of human spoken-word
    recognition, its speech recognition performance is not
    comparable to that of human performance, possibly due to
    suboptimal intermediate articulatory feature (AF)
    representations. This study investigates the effect of improved
    AF representations, obtained using a state-of-the-art deep
    convolutional network, on Fine-Tracker’s simulation and
    recognition performance: Although the improved AF quality
    resulted in improved speech recognition; it, surprisingly, did
    not lead to an improvement in Fine-Tracker’s simulation power.
  • Schiller, N. O., Van Lieshout, P. H. H. M., Meyer, A. S., & Levelt, W. J. M. (1997). Is the syllable an articulatory unit in speech production? Evidence from an Emma study. In P. Wille (Ed.), Fortschritte der Akustik: Plenarvorträge und Fachbeiträge der 23. Deutschen Jahrestagung für Akustik (DAGA 97) (pp. 605-606). Oldenburg: DEGA.
  • Schuller, B., Steidl, S., Batliner, A., Bergelson, E., Krajewski, J., Janott, C., Amatuni, A., Casillas, M., Seidl, A., Soderstrom, M., Warlaumont, A. S., Hidalgo, G., Schnieder, S., Heiser, C., Hohenhorst, W., Herzog, M., Schmitt, M., Qian, K., Zhang, Y., Trigeorgis, G. and 2 moreSchuller, B., Steidl, S., Batliner, A., Bergelson, E., Krajewski, J., Janott, C., Amatuni, A., Casillas, M., Seidl, A., Soderstrom, M., Warlaumont, A. S., Hidalgo, G., Schnieder, S., Heiser, C., Hohenhorst, W., Herzog, M., Schmitt, M., Qian, K., Zhang, Y., Trigeorgis, G., Tzirakis, P., & Zafeiriou, S. (2017). The INTERSPEECH 2017 computational paralinguistics challenge: Addressee, cold & snoring. In Proceedings of Interspeech 2017 (pp. 3442-3446). doi:10.21437/Interspeech.2017-43.

    Abstract

    The INTERSPEECH 2017 Computational Paralinguistics Challenge addresses three different problems for the first time in research competition under well-defined conditions: In the Addressee sub-challenge, it has to be determined whether speech produced by an adult is directed towards another adult or towards a child; in the Cold sub-challenge, speech under cold has to be told apart from ‘healthy’ speech; and in the Snoring subchallenge, four different types of snoring have to be classified. In this paper, we describe these sub-challenges, their conditions, and the baseline feature extraction and classifiers, which include data-learnt feature representations by end-to-end learning with convolutional and recurrent neural networks, and bag-of-audiowords for the first time in the challenge series
  • Sekine, K. (2017). Gestural hesitation reveals children’s competence on multimodal communication: Emergence of disguised adaptor. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (CogSci 2017) (pp. 3113-3118). Austin, TX: Cognitive Science Society.

    Abstract

    Speakers sometimes modify their gestures during the process of production into adaptors such as hair touching or eye scratching. Such disguised adaptors are evidence that the speaker can monitor their gestures. In this study, we investigated when and how disguised adaptors are first produced by children. Sixty elementary school children participated in this study (ten children in each age group; from 7 to 12 years old). They were instructed to watch a cartoon and retell it to their parents. The results showed that children did not produce disguised adaptors until the age of 8. The disguised adaptors accompany fluent speech until the children are 10 years old and accompany dysfluent speech until they reach 11 or 12 years of age. These results suggest that children start to monitor their gestures when they are 9 or 10 years old. Cognitive changes were considered as factors to influence emergence of disguised adaptors
  • Seuren, P. A. M. (1980). Variabele competentie: Linguïstiek en sociolinguïstiek anno 1980. In Handelingen van het 36e Nederlands Filologencongres: Gehouden te Groningen op woensdag 9, donderdag 10 en vrijdag 11 April 1980 (pp. 41-56). Amsterdam: Holland University Press.
  • 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.
  • 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
  • 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.
  • 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.
  • 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
  • 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.
  • 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 de Weijer, J. (1997). Language input to a prelingual infant. In A. Sorace, C. Heycock, & R. Shillcock (Eds.), Proceedings of the GALA '97 conference on language acquisition (pp. 290-293). Edinburgh University Press.

    Abstract

    Pitch, intonation, and speech rate were analyzed in a collection of everyday speech heard by one Dutch infant between the ages of six and nine months. Components of each of these variables were measured in the speech of three adult speakers (mother, father, baby-sitter) when they addressed the infant, and when they addressed another adult. The results are in line with previously reported findings which are usually based on laboratory or prearranged settings: infant-directed speech in a natural setting exhibits more pitch variation, a larger number of simple intonation contours, and slower speech rate than does adult-directed speech.
  • Van Heuven, V. J., Haan, J., Janse, E., & Van der Torre, E. J. (1997). Perceptual identification of sentence type and the time-distribution of prosodic interrogativity markers in Dutch. In Proceedings of the ESCA Tutorial and Research Workshop on Intonation: Theory, Models and Applications, Athens, Greece, 1997 (pp. 317-320).

    Abstract

    Dutch distinguishes at least four sentence types: statements and questions, the latter type being subdivided into wh-questions (beginning with a question word), yes/no-questions (with inversion of subject and finite), and declarative questions (lexico-syntactically identical to statement). Acoustically, each of these (sub)types was found to have clearly distinct global F0-patterns, as well as a characteristic distribution of final rises [1,2]. The present paper explores the separate contribution of parameters of global downtrend and size of accent-lending pitch movements versus aspects of the terminal rise to the human identification of the four sentence (sub)types, at various positions in the time-course of the utterance. The results show that interrogativity in Dutch can be identified at an early point in the utterance. However, wh-questions are not distinct from statements.

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