Publications

Displaying 1 - 100 of 121
  • Allerhand, M., Butterfield, S., Cutler, A., & Patterson, R. (1992). Assessing syllable strength via an auditory model. In Proceedings of the Institute of Acoustics: Vol. 14 Part 6 (pp. 297-304). St. Albans, Herts: Institute of Acoustics.
  • 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
  • Bauer, B. L. M. (1992). Evolution in language: Evidence from the Romance auxiliary. In B. Chiarelli, J. Wind, A. Nocentini, & B. Bichakjian (Eds.), Language origin: A multidisciplinary approach (pp. 517-528). Dordrecht: Kluwer.
  • 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.
  • Blythe, J. (2018). Genesis of the trinity: The convergent evolution of trirelational kinterms. In P. McConvell, & P. Kelly (Eds.), Skin, kin and clan: The dynamics of social categories in Indigenous Australia (pp. 431-471). Canberra: ANU EPress.
  • Bowerman, M., & Pederson, E. (1992). Topological relations picture series. In S. C. Levinson (Ed.), Space stimuli kit 1.2 (pp. 51). Nijmegen: Max Planck Institute for Psycholinguistics. doi:10.17617/2.883589.

    Abstract

    This task is designed to elicit expressions of spatial relations. It was originally designed by Melissa Bowerman for use with young children, but was then developed further by Bowerman in collaboration with Pederson for crosslinguistic comparison. It has been used in fieldsites all over the world and is commonly known as “BowPed” or “TPRS”. Older incarnations did not always come with instructions. This entry includes a one-page instruction sheet and high quality versions of the original pictures.
  • Bowerman, M. (1992). Topological Relations Pictures: Topological Paths. In S. C. Levinson (Ed.), Space stimuli kit 1.2 (pp. 18-24). Nijmegen: Max Planck Institute for Psycholinguistics. doi:10.17617/2.3512508.

    Abstract

    This entry suggests ways to elicit descriptions of caused motion involving topological relations (the domain of English put IN/ON/TOGETHER, take OUT/OFF/APART, etc.). There is a large amount of cross-linguistic variation in this domain. The tasks outlined here address matters such as the division of labor between the various elements of spatial semantics in the sentence. For example, is most of the work of expressing PATH done in a locative marker, or in the verb, or both?
  • Bowerman, M. (1992). Topological Relations Pictures: Static Relations. In S. C. Levinson (Ed.), Space stimuli kit 1.2 (pp. 25-28). Nijmegen: Max Planck Institute for Psycholinguistics. doi:10.17617/2.3512672.

    Abstract

    The precursor to the Bowped stimuli, this entry suggests various spatial configurations to explore using real objects, rather than the line drawings used in Bowped.
  • Brand, J., Monaghan, P., & Walker, P. (2018). Changing Signs: Testing How Sound-Symbolism Supports Early Word Learning. In C. Kalish, M. Rau, J. Zhu, & T. T. Rogers (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (CogSci 2018) (pp. 1398-1403). Austin, TX: Cognitive Science Society.

    Abstract

    Learning a language involves learning how to map specific forms onto their associated meanings. Such mappings can utilise arbitrariness and non-arbitrariness, yet, our understanding of how these two systems operate at different stages of vocabulary development is still not fully understood. The Sound-Symbolism Bootstrapping Hypothesis (SSBH) proposes that sound-symbolism is essential for word learning to commence, but empirical evidence of exactly how sound-symbolism influences language learning is still sparse. It may be the case that sound-symbolism supports acquisition of categories of meaning, or that it enables acquisition of individualized word meanings. In two Experiments where participants learned form-meaning mappings from either sound-symbolic or arbitrary languages, we demonstrate the changing roles of sound-symbolism and arbitrariness for different vocabulary sizes, showing that sound-symbolism provides an advantage for learning of broad categories, which may then transfer to support learning individual words, whereas an arbitrary language impedes acquisition of categories of sound to meaning.
  • Brehm, L., & Goldrick, M. (2018). Connectionist principles in theories of speech production. In S.-A. Rueschemeyer, & M. G. Gaskell (Eds.), The Oxford Handbook of Psycholinguistics (2nd ed., pp. 372-397). Oxford: Oxford University Press.

    Abstract

    This chapter focuses on connectionist modeling in language production, highlighting how
    core principles of connectionism provide coverage for empirical observations about
    representation and selection at the phonological, lexical, and sentence levels. The first
    section focuses on the connectionist principles of localist representations and spreading
    activation. It discusses how these two principles have motivated classic models of speech
    production and shows how they cover results of the picture-word interference paradigm,
    the mixed error effect, and aphasic naming errors. The second section focuses on how
    newer connectionist models incorporate the principles of learning and distributed
    representations through discussion of syntactic priming, cumulative semantic
    interference, sequencing errors, phonological blends, and code-switching
  • Brown, P., & Levinson, S. C. (2018). Tzeltal: The demonstrative system. In S. C. Levinson, S. Cutfield, M. Dunn, N. J. Enfield, & S. Meira (Eds.), Demonstratives in cross-linguistic perspective (pp. 150-177). Cambridge: Cambridge University Press.
  • 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.
  • Coenen, J., & Klein, W. (1992). The acquisition of Dutch. In W. Klein, & C. Perdue (Eds.), Utterance structure: Developing grammars again (pp. 189-224). Amsterdam: Benjamins.
  • 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.
  • Ip, M. H. K., & Cutler, A. (2018). Cue equivalence in prosodic entrainment for focus detection. In J. Epps, J. Wolfe, J. Smith, & C. Jones (Eds.), Proceedings of the 17th Australasian International Conference on Speech Science and Technology (pp. 153-156).

    Abstract

    Using a phoneme detection task, the present series of
    experiments examines whether listeners can entrain to
    different combinations of prosodic cues to predict where focus
    will fall in an utterance. The stimuli were recorded by four
    female native speakers of Australian English who happened to
    have used different prosodic cues to produce sentences with
    prosodic focus: a combination of duration cues, mean and
    maximum F0, F0 range, and longer pre-target interval before
    the focused word onset, only mean F0 cues, only pre-target
    interval, and only duration cues. Results revealed that listeners
    can entrain in almost every condition except for where
    duration was the only reliable cue. Our findings suggest that
    listeners are flexible in the cues they use for focus processing.
  • Cutler, A. (1970). An experimental method for semantic field study. Linguistic Communications, 2, 87-94.

    Abstract

    This paper emphasizes the need for empirical research and objective discovery procedures in semantics, and illustrates a method by which these goals may be obtained. The aim of the methodology described is to provide a description of the internal structure of a semantic field by eliciting the description--in an objective, standardized manner--from a representative group of native speakers. This would produce results that would be equally obtainable by any linguist using the same method under the same conditions with a similarly representative set of informants. The standardized method suggested by the author is the Semantic Differential developed by C. E. Osgood in the 1950's. Applying this method to semantic research, it is further hypothesized that, should different members of a semantic field be employed as concepts on a Semantic Differential task, a factor analysis of the results would reveal the dimensions operative within the body of data. The author demonstrates the use of the Semantic Differential and factor analysis in an actual experiment.
  • 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., Kearns, R., Norris, D., & Scott, D. (1992). Listeners’ responses to extraneous signals coincident with English and French speech. In J. Pittam (Ed.), Proceedings of the 4th Australian International Conference on Speech Science and Technology (pp. 666-671). Canberra: Australian Speech Science and Technology Association.

    Abstract

    English and French listeners performed two tasks - click location and speeded click detection - with both English and French sentences, closely matched for syntactic and phonological structure. Clicks were located more accurately in open- than in closed-class words in both English and French; they were detected more rapidly in open- than in closed-class words in English, but not in French. The two listener groups produced the same pattern of responses, suggesting that higher-level linguistic processing was not involved in these tasks.
  • Cutler, A., & Farrell, J. (2018). Listening in first and second language. In J. I. Liontas (Ed.), The TESOL encyclopedia of language teaching. New York: Wiley. doi:10.1002/9781118784235.eelt0583.

    Abstract

    Listeners' recognition of spoken language involves complex decoding processes: The continuous speech stream must be segmented into its component words, and words must be recognized despite great variability in their pronunciation (due to talker differences, or to influence of phonetic context, or to speech register) and despite competition from many spuriously present forms supported by the speech signal. L1 listeners deal more readily with all levels of this complexity than L2 listeners. Fortunately, the decoding processes necessary for competent L2 listening can be taught in the classroom. Evidence-based methodologies targeted at the development of efficient speech decoding include teaching of minimal pairs, of phonotactic constraints, and of reduction processes, as well as the use of dictation and L2 video captions.
  • Cutler, A. (1992). Processing constraints of the native phonological repertoire on the native language. In Y. Tohkura, E. Vatikiotis-Bateson, & Y. Sagisaka (Eds.), Speech perception, production and linguistic structure (pp. 275-278). Tokyo: Ohmsha.
  • Cutler, A. (1992). Psychology and the segment. In G. Docherty, & D. Ladd (Eds.), Papers in laboratory phonology II: Gesture, segment, prosody (pp. 290-295). Cambridge: Cambridge University Press.
  • Cutler, A., & Robinson, T. (1992). Response time as a metric for comparison of speech recognition by humans and machines. In J. Ohala, T. Neary, & B. Derwing (Eds.), Proceedings of the Second International Conference on Spoken Language Processing: Vol. 1 (pp. 189-192). Alberta: University of Alberta.

    Abstract

    The performance of automatic speech recognition systems is usually assessed in terms of error rate. Human speech recognition produces few errors, but relative difficulty of processing can be assessed via response time techniques. We report the construction of a measure analogous to response time in a machine recognition system. This measure may be compared directly with human response times. We conducted a trial comparison of this type at the phoneme level, including both tense and lax vowels and a variety of consonant classes. The results suggested similarities between human and machine processing in the case of consonants, but differences in the case of vowels.
  • Cutler, A. (1992). The perception of speech: Psycholinguistic aspects. In W. Bright (Ed.), International encyclopedia of language: Vol. 3 (pp. 181-183). New York: Oxford University Press.
  • Cutler, A. (1992). The production and perception of word boundaries. In Y. Tohkura, E. Vatikiotis-Bateson, & Y. Sagisaka (Eds.), Speech perception, production and linguistic structure (pp. 419-425). Tokyo: Ohsma.
  • Cutler, A. (1992). Why not abolish psycholinguistics? In W. Dressler, H. Luschützky, O. Pfeiffer, & J. Rennison (Eds.), Phonologica 1988 (pp. 77-87). Cambridge: Cambridge University Press.
  • Delgado, T., Ravignani, A., Verhoef, T., Thompson, B., Grossi, T., & Kirby, S. (2018). Cultural transmission of melodic and rhythmic universals: Four experiments and a model. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 89-91). Toruń, Poland: NCU Press. doi:10.12775/3991-1.019.
  • Dingemanse, M., Blythe, J., & Dirksmeyer, T. (2018). Formats for other-initiation of repair across languages: An exercise in pragmatic typology. In I. Nikolaeva (Ed.), Linguistic Typology: Critical Concepts in Linguistics. Vol. 4 (pp. 322-357). London: Routledge.

    Abstract

    In conversation, people regularly deal with problems of speaking, hearing, and understanding. We report on a cross-linguistic investigation of the conversational structure of other-initiated repair (also known as collaborative repair, feedback, requests for clarification, or grounding sequences). We take stock of formats for initiating repair across languages (comparable to English huh?, who?, y’mean X?, etc.) and find that different languages make available a wide but remarkably similar range of linguistic resources for this function. We exploit the patterned variation as evidence for several underlying concerns addressed by repair initiation: characterising trouble, managing responsibility, and handling knowledge. The concerns do not always point in the same direction and thus provide participants in interaction with alternative principles for selecting one format over possible others. By comparing conversational structures across languages, this paper contributes to pragmatic typology: the typology of systems of language use and the principles that shape them.
  • Duarte, R., Uhlmann, M., Van den Broek, D., Fitz, H., Petersson, K. M., & Morrison, A. (2018). Encoding symbolic sequences with spiking neural reservoirs. In Proceedings of the 2018 International Joint Conference on Neural Networks (IJCNN). doi:10.1109/IJCNN.2018.8489114.

    Abstract

    Biologically inspired spiking networks are an important tool to study the nature of computation and cognition in neural systems. In this work, we investigate the representational capacity of spiking networks engaged in an identity mapping task. We compare two schemes for encoding symbolic input, one in which input is injected as a direct current and one where input is delivered as a spatio-temporal spike pattern. We test the ability of networks to discriminate their input as a function of the number of distinct input symbols. We also compare performance using either membrane potentials or filtered spike trains as state variable. Furthermore, we investigate how the circuit behavior depends on the balance between excitation and inhibition, and the degree of synchrony and regularity in its internal dynamics. Finally, we compare different linear methods of decoding population activity onto desired target labels. Overall, our results suggest that even this simple mapping task is strongly influenced by design choices on input encoding, state-variables, circuit characteristics and decoding methods, and these factors can interact in complex ways. This work highlights the importance of constraining computational network models of behavior by available neurobiological evidence.
  • Eisner, F., & McQueen, J. M. (2018). Speech perception. In S. Thompson-Schill (Ed.), Stevens’ handbook of experimental psychology and cognitive neuroscience (4th ed.). Volume 3: Language & thought (pp. 1-46). Hoboken: Wiley. doi:10.1002/9781119170174.epcn301.

    Abstract

    This chapter reviews the computational processes that are responsible for recognizing word forms in the speech stream. We outline the different stages in a processing hierarchy from the extraction of general acoustic features, through speech‐specific prelexical processes, to the retrieval and selection of lexical representations. We argue that two recurring properties of the system as a whole are abstraction and adaptability. We also present evidence for parallel processing of information on different timescales, more specifically that segmental material in the speech stream (its consonants and vowels) is processed in parallel with suprasegmental material (the prosodic structures of spoken words). We consider evidence from both psycholinguistics and neurobiology wherever possible, and discuss how the two fields are beginning to address common computational problems. The challenge for future research in speech perception will be to build an account that links these computational problems, through functional mechanisms that address them, to neurobiological implementation.
  • Ergin, R., Senghas, A., Jackendoff, R., & Gleitman, L. (2018). Structural cues for symmetry, asymmetry, and non-symmetry in Central Taurus Sign Language. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 104-106). Toruń, Poland: NCU Press. doi:10.12775/3991-1.025.
  • Ernestus, M., & Smith, R. (2018). Qualitative and quantitative aspects of phonetic variation in Dutch eigenlijk. In F. Cangemi, M. Clayards, O. Niebuhr, B. Schuppler, & M. Zellers (Eds.), Rethinking reduction: Interdisciplinary perspectives on conditions, mechanisms, and domains for phonetic variation (pp. 129-163). Berlin/Boston: De Gruyter Mouton.
  • Flecken, M., & Von Stutterheim, C. (2018). Sprache und Kognition: Sprachvergleichende und lernersprachliche Untersuchungen zur Ereigniskonzeptualisierung. In S. Schimke, & H. Hopp (Eds.), Sprachverarbeitung im Zweitspracherwerb (pp. 325-356). Berlin: De Gruyter. doi:10.1515/9783110456356-014.
  • Floyd, S. (2018). Egophoricity and argument structure in Cha'palaa. In S. Floyd, E. Norcliffe, & L. San Roque (Eds.), Egophoricity (pp. 269-304). Amsterdam: Benjamins.

    Abstract

    The Cha’palaa language of Ecuador (Barbacoan) features verbal morphology for marking knowledge-based categories that, in usage, show a variant of the cross-linguistically recurrent pattern of ‘egophoric distribution': specific forms associate with speakers in contrast to others in statements and with addressees in contrast to others in questions. These are not person markers, but rather are used by speakers to portray their involvement in states of affairs as active, agentive participants (ego) versus other types of involvement (non-ego). They interact with person and argument structure, but through pragmatic ‘person sensitivities’ rather than through grammatical agreement. Not only does this pattern appear in verbal morphology, it also can be observed in alternations of predicate construction types and case alignment, helping to show how egophoric marking is a pervasive element of Cha'palaa's linguistic system. This chapter gives a first account of egophoricity in Cha’palaa, beginning with a discussion of person sensitivity, egophoric distribution, and issues of flexibility of marking with respect to degree of volition or control. It then focuses on a set of intransitive experiencer (or ‘endopathic') predicates that refer to internal states which mark egophoric values for the undergoer role, not the actor role, showing ‘quirky’ accusative marking instead of nominative case. It concludes with a summary of how egophoricity in Cha'palaa interacts with issues of argument structure in comparison to a language with person agreement, here represented by examples from Cha’palaa’s neighbor Ecuadorian Highland Quechua.
  • Forkel, S. J., & Catani, M. (2018). Structural Neuroimaging. In A. De Groot, & P. Hagoort (Eds.), Research Methods in Psycholinguistics and the Neurobiology of Language: A Practical Guide (pp. 288-308). Hoboken: Wiley. doi:10.1002/9781394259762.ch15.

    Abstract

    Structural imaging based on computerized tomography (CT) and magnetic resonance imaging (MRI) has progressively replaced traditional post‐mortem studies in the process of identifying the neuroanatomical basis of language. In the clinical setting, the information provided by structural imaging has been used to confirm the exact diagnosis and formulate an individualized treatment plan. In the research arena, neuroimaging has permitted to understand neuroanatomy at the individual and group level. The possibility to obtain quantitative measures of lesions has improved correlation analyses between severity of symptoms, lesion load, and lesion location. More recently, the development of structural imaging based on diffusion MRI has provided valid solutions to two major limitations of more conventional imaging. In stroke patients, diffusion can visualize early changes due to a stroke that are otherwise not detectable with more conventional structural imaging, with important implications for the clinical management of acute stroke patients. Beyond the sensitivity to early changes, diffusion imaging tractography presents the possibility of visualizing the trajectories of individual white matter pathways connecting distant regions. A pathway analysis based on tractography is offering a new perspective in neurolinguistics. First, it permits to formulate new anatomical models of language function in the healthy brain and allows to directly test these models in the human population without any reliance on animal models. Second, by defining the exact location of the damage to specific white matter connections we can understand the contribution of different mechanisms to the emergence of language deficits (e.g., cortical versus disconnection mechanisms). Finally, a better understanding of the anatomical variability of different language networks is helping to identify new anatomical predictors of language recovery. In this chapter we will focus on the principles of structural MRI and, in particular, diffusion imaging and tractography and present examples of how these methods have informed our understanding of variance in language performances in the healthy brain and language deficits in patient populations.
  • 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.
  • Gingras, B., Honing, H., Peretz, I., Trainor, L. J., & Fisher, S. E. (2018). Defining the biological bases of individual differences in musicality. In H. Honing (Ed.), The origins of musicality (pp. 221-250). Cambridge, MA: MIT Press.
  • Hammarström, H. (2018). Language isolates in the New Guinea region. In L. Campbell (Ed.), Language Isolates (pp. 287-322). London: Routledge.
  • Hoey, E., & Kendrick, K. H. (2018). Conversation analysis. In A. M. B. De Groot, & P. Hagoort (Eds.), Research methods in psycholinguistics and the neurobiology of language: A practical guide (pp. 151-173). Hoboken: Wiley.

    Abstract

    Conversation Analysis (CA) is an inductive, micro-analytic, and predominantly qualitative
    method for studying human social interactions. This chapter describes and illustrates the basic
    methods of CA. We first situate the method by describing its sociological foundations, key areas
    of analysis, and particular approach in using naturally occurring data. The bulk of the chapter is
    devoted to practical explanations of the typical conversation analytic process for collecting data
    and producing an analysis. We analyze a candidate interactional practice – the assessmentimplicative
    interrogative – using real data extracts as a demonstration of the method, explicitly
    laying out the relevant questions and considerations for every stage of an analysis. The chapter
    concludes with some discussion of quantitative approaches to conversational interaction, and
    links between CA and psycholinguistic concerns
  • Hopman, E., Thompson, B., Austerweil, J., & Lupyan, G. (2018). Predictors of L2 word learning accuracy: A big data investigation. In C. Kalish, M. Rau, J. Zhu, & T. T. Rogers (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (CogSci 2018) (pp. 513-518). Austin, TX: Cognitive Science Society.

    Abstract

    What makes some words harder to learn than others in a second language? Although some robust factors have been identified based on small scale experimental studies, many relevant factors are difficult to study in such experiments due to the amount of data necessary to test them. Here, we investigate what factors affect the ease of learning of a word in a second language using a large data set of users learning English as a second language through the Duolingo mobile app. In a regression analysis, we test and confirm the well-studied effect of cognate status on word learning accuracy. Furthermore, we find significant effects for both cross-linguistic semantic alignment and English semantic density, two novel predictors derived from large scale distributional models of lexical semantics. Finally, we provide data on several other psycholinguistically plausible word level predictors. We conclude with a discussion of the limits, benefits and future research potential of using big data for investigating second language learning.
  • Indefrey, P. (2018). The relationship between syntactic production and comprehension. In S.-A. Rueschemeyer, & M. G. Gaskell (Eds.), The Oxford Handbook of Psycholinguistics (2nd ed., pp. 486-505). Oxford: Oxford University Press.

    Abstract

    This chapter deals with the question of whether there is one syntactic system that is shared by language production and comprehension or whether there are two separate systems. It first discusses arguments in favor of one or the other option and then presents the current evidence on the brain structures involved in sentence processing. The results of meta-analyses of numerous neuroimaging studies suggest that there is one system consisting of functionally distinct cortical regions: the dorsal part of Broca’s area subserving compositional syntactic processing; the ventral part of Broca’s area subserving compositional semantic processing; and the left posterior temporal cortex (Wernicke’s area) subserving the retrieval of lexical syntactic and semantic information. Sentence production, the comprehension of simple and complex sentences, and the parsing of sentences containing grammatical violations differ with respect to the recruitment of these functional components.
  • Isbilen, E., Frost, R. L. A., Monaghan, P., & Christiansen, M. (2018). Bridging artificial and natural language learning: Comparing processing- and reflection-based measures of learning. In C. Kalish, M. Rau, J. Zhu, & T. T. Rogers (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (CogSci 2018) (pp. 1856-1861). Austin, TX: Cognitive Science Society.

    Abstract

    A common assumption in the cognitive sciences is that artificial and natural language learning rely on shared mechanisms. However, attempts to bridge the two have yielded ambiguous results. We suggest that an empirical disconnect between the computations employed during learning and the methods employed at test may explain these mixed results. Further, we propose statistically-based chunking as a potential computational link between artificial and natural language learning. We compare the acquisition of non-adjacent dependencies to that of natural language structure using two types of tasks: reflection-based 2AFC measures, and processing-based recall measures, the latter being more computationally analogous to the processes used during language acquisition. Our results demonstrate that task-type significantly influences the correlations observed between artificial and natural language acquisition, with reflection-based and processing-based measures correlating within – but not across – task-type. These findings have fundamental implications for artificial-to-natural language comparisons, both methodologically and theoretically.
  • Janssen, R., Moisik, S. R., & Dediu, D. (2018). Agent model reveals the influence of vocal tract anatomy on speech during ontogeny and glossogeny. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 171-174). Toruń, Poland: NCU Press. doi:10.12775/3991-1.042.
  • Janssen, R., & Dediu, D. (2018). Genetic biases affecting language: What do computer models and experimental approaches suggest? In T. Poibeau, & A. Villavicencio (Eds.), Language, Cognition and Computational Models (pp. 256-288). Cambridge: Cambridge University Press.

    Abstract

    Computer models of cultural evolution have shown language properties emerging on interacting agents with a brain that lacks dedicated, nativist language modules. Notably, models using Bayesian agents provide a precise specification of (extra-)liguististic factors (e.g., genetic) that shape language through iterated learning (biases on language), and demonstrate that weak biases get expressed more strongly over time (bias amplification). Other models attempt to lessen assumption on agents’ innate predispositions even more, and emphasize self-organization within agents, highlighting glossogenesis (the development of language from a nonlinguistic state). Ultimately however, one also has to recognize that biology and culture are strongly interacting, forming a coevolving system. As such, computer models show that agents might (biologically) evolve to a state predisposed to language adaptability, where (culturally) stable language features might get assimilated into the genome via Baldwinian niche construction. In summary, while many questions about language evolution remain unanswered, it is clear that it is not to be completely understood from a purely biological, cognitivist perspective. Language should be regarded as (partially) emerging on the social interactions between large populations of speakers. In this context, agent models provide a sound approach to investigate the complex dynamics of genetic biasing on language and speech
  • 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
  • Kempen, G., & Vosse, T. (1992). A language-sensitive text editor for Dutch. In P. O’Brian Holt, & N. Williams (Eds.), Computers and writing: State of the art (pp. 68-77). Dordrecht: Kluwer Academic Publishers.

    Abstract

    Modern word processors begin to offer a range of facilities for spelling, grammar and style checking in English. For the Dutch language hardly anything is available as yet. Many commercial word processing packages do include a hyphenation routine and a lexicon-based spelling checker but the practical usefulness of these tools is limited due to certain properties of Dutch orthography, as we will explain below. In this chapter we describe a text editor which incorporates a great deal of lexical, morphological and syntactic knowledge of Dutch and monitors the orthographical quality of Dutch texts. Section 1 deals with those aspects of Dutch orthography which pose problems to human authors as well as to computational language sensitive text editing tools. In section 2 we describe the design and the implementation of the text editor we have built. Section 3 is mainly devoted to a provisional evaluation of the system.
  • Kempen, G. (1992). Generation. In W. Bright (Ed.), International encyclopedia of linguistics (pp. 59-61). New York: Oxford University Press.
  • Kempen, G. (1992). Language technology and language instruction: Computational diagnosis of word level errors. In M. Swartz, & M. Yazdani (Eds.), Intelligent tutoring systems for foreign language learning: The bridge to international communication (pp. 191-198). Berlin: Springer.
  • Kempen, G. (1992). Second language acquisition as a hybrid learning process. In F. Engel, D. Bouwhuis, T. Bösser, & G. d'Ydewalle (Eds.), Cognitive modelling and interactive environments in language learning (pp. 139-144). Berlin: Springer.
  • Klein, W. (1992). Der Fall Horten gegen Delius, oder: Der Laie, der Fachmann und das Recht. In G. Grewendorf (Ed.), Rechtskultur als Sprachkultur: Zur forensischen Funktion der Sprachanalyse (pp. 284-313). Frankfurt am Main: Suhrkamp.
  • Klein, W., & Perdue, C. (1992). Framework. In W. Klein, & C. Perdue (Eds.), Utterance structure: Developing grammars again (pp. 11-59). Amsterdam: Benjamins.
  • Klein, W., & Carroll, M. (1992). The acquisition of German. In W. Klein, & C. Perdue (Eds.), Utterance structure: Developing grammars again (pp. 123-188). Amsterdam: Benjamins.
  • De Kovel, C. G. F., & Fisher, S. E. (2018). Molecular genetic methods. In A. M. B. De Groot, & P. Hagoort (Eds.), Research methods in psycholinguistics and the neurobiology of language: A practical guide (pp. 330-353). Hoboken: Wiley.
  • Lattenkamp, E. Z., Vernes, S. C., & Wiegrebe, L. (2018). Mammalian models for the study of vocal learning: A new paradigm in bats. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 235-237). Toruń, Poland: NCU Press. doi:10.12775/3991-1.056.
  • Lauscher, A., Eckert, K., Galke, L., Scherp, A., Rizvi, S. T. R., Ahmed, S., Dengel, A., Zumstein, P., & Klein, A. (2018). Linked open citation database: Enabling libraries to contribute to an open and interconnected citation graph. In J. Chen, M. A. Gonçalves, J. M. Allen, E. A. Fox, M.-Y. Kan, & V. Petras (Eds.), JCDL '18: Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries (pp. 109-118). New York: ACM. doi:10.1145/3197026.3197050.

    Abstract

    Citations play a crucial role in the scientific discourse, in information retrieval, and in bibliometrics. Many initiatives are currently promoting the idea of having free and open citation data. Creation of citation data, however, is not part of the cataloging workflow in libraries nowadays.
    In this paper, we present our project Linked Open Citation Database, in which we design distributed processes and a system infrastructure based on linked data technology. The goal is to show that efficiently cataloging citations in libraries using a semi-automatic approach is possible. We specifically describe the current state of the workflow and its implementation. We show that we could significantly improve the automatic reference extraction that is crucial for the subsequent data curation. We further give insights on the curation and linking process and provide evaluation results that not only direct the further development of the project, but also allow us to discuss its overall feasibility.
  • Lefever, E., Hendrickx, I., Croijmans, I., Van den Bosch, A., & Majid, A. (2018). Discovering the language of wine reviews: A text mining account. In N. Calzolari, K. Choukri, C. Cieri, T. Declerck, S. Goggi, K. Hasida, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk, S. Piperidis, & T. Tokunaga (Eds.), Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018) (pp. 3297-3302). Paris: LREC.

    Abstract

    It is widely held that smells and flavors are impossible to put into words. In this paper we test this claim by seeking predictive patterns in wine reviews, which ostensibly aim to provide guides to perceptual content. Wine reviews have previously been critiqued as random and meaningless. We collected an English corpus of wine reviews with their structured metadata, and applied machine learning techniques to automatically predict the wine's color, grape variety, and country of origin. To train the three supervised classifiers, three different information sources were incorporated: lexical bag-of-words features, domain-specific terminology features, and semantic word embedding features. In addition, using regression analysis we investigated basic review properties, i.e., review length, average word length, and their relationship to the scalar values of price and review score. Our results show that wine experts do share a common vocabulary to describe wines and they use this in a consistent way, which makes it possible to automatically predict wine characteristics based on the review text alone. This means that odors and flavors may be more expressible in language than typically acknowledged.
  • Levelt, W. J. M. (1970). A scaling approach to the study of syntactic relations. In G. B. Flores d'Arcais, & W. J. M. Levelt (Eds.), Advances in psycholinguistics (pp. 109-121). Amsterdam: North Holland.
  • Levelt, W. J. M. (1962). Motion breaking and the perception of causality. In A. Michotte (Ed.), Causalité, permanence et réalité phénoménales: Etudes de psychologie expérimentale (pp. 244-258). Louvain: Publications Universitaires.
  • Levelt, W. J. M., & Plomp, R. (1962). Musical consonance and critical bandwidth. In Proceedings of the 4th International Congress Acoustics (pp. 55-55).
  • Levelt, W. J. M. (1970). Hierarchical clustering algorithms in the psychology of grammar. In G. B. Flores d'Arcais, & W. J. M. Levelt (Eds.), Advances in psycholinguistics (pp. 101-108). Amsterdam: North Holland.
  • Levelt, W. J. M. (1992). Psycholinguistics: An overview. In W. Bright (Ed.), International encyclopedia of linguistics (Vol. 3) (pp. 290-294). Oxford: Oxford University Press.
  • Levelt, W. J. M., & Plomp, K. (1968). The appreciation of musical intervals. In J. M. M. Aler (Ed.), Proceedings of the fifth International Congress of Aesthetics, Amsterdam 1964 (pp. 901-904). The Hague: Mouton.
  • Levinson, S. C. (1992). Space in Australian Languages Questionnaire. In S. C. Levinson (Ed.), Space stimuli kit 1.2 (pp. 29-40). Nijmegen: Max Planck Institute for Psycholinguistics.

    Abstract

    This questionnaire is designed to explore how spatial relations are encoded in Australian language, but may be of interest to researchers further afield.
  • Levinson, S. C. (1992). Space in Australian Languages Questionnaire. In S. C. Levinson (Ed.), Space stimuli kit 1.2 (pp. 29-40). Nijmegen: Max Planck Institute for Psycholinguistics. doi:10.17617/2.3512641.

    Abstract

    This questionnaire is designed to explore how spatial relations are encoded in Australian language, but may be of interest to researchers further afield.
  • Levinson, S. C. (1992). Activity types and language. In P. Drew, & J. Heritage (Eds.), Talk at work: Interaction in institutional settings (pp. 66-100). Cambridge University Press.
  • Levinson, S. C., Brown, P., Danzinger, E., De León, L., Haviland, J. B., Pederson, E., & Senft, G. (1992). Man and Tree & Space Games. In S. C. Levinson (Ed.), Space stimuli kit 1.2 (pp. 7-14). Nijmegen: Max Planck Institute for Psycholinguistics. doi:10.17617/2.2458804.

    Abstract

    These classic tasks can be used to explore spatial reference in field settings. They provide a language-independent metric for eliciting spatial language, using a “director-matcher” paradigm. The Man and Tree task deals with location on the horizontal plane with both featured (man) and non-featured (e.g., tree) objects. The Space Games depict various objects (e.g. bananas, lemons) and elicit spatial contrasts not obviously lexicalisable in English.
  • Levinson, S. C. (2018). Introduction: Demonstratives: Patterns in diversity. In S. C. Levinson, S. Cutfield, M. Dunn, N. J. Enfield, & S. Meira (Eds.), Demonstratives in cross-linguistic perspective (pp. 1-42). Cambridge: Cambridge University Press.
  • Levinson, S. C., & Annamalai, E. (1992). Why presuppositions aren't conventional. In R. N. Srivastava (Ed.), Language and text: Studies in honour of Ashok R. Kelkar (pp. 227-242). Dehli: Kalinga Publications.
  • Levinson, S. C. (2018). Yélî Dnye: Demonstratives in the language of Rossel Island, Papua New Guinea. In S. C. Levinson, S. Cutfield, M. Dunn, N. J. Enfield, & S. Meira (Eds.), Demonstratives in cross-linguistic perspective (pp. 318-342). Cambridge: Cambridge University Press.
  • 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%.
  • Majid, A. (2018). Cultural factors shape olfactory language [Reprint]. In D. Howes (Ed.), Senses and Sensation: Critical and Primary Sources. Volume 3 (pp. 307-310). London: Bloomsbury Publishing.
  • Majid, A. (2018). Language and cognition. In H. Callan (Ed.), The International Encyclopedia of Anthropology. Hoboken: John Wiley & Sons Ltd.

    Abstract

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

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  • Mamus, E., & Karadöller, D. Z. (2018). Anıları Zihinde Canlandırma [Imagery in autobiographical memories]. In S. Gülgöz, B. Ece, & S. Öner (Eds.), Hayatı Hatırlamak: Otobiyografik Belleğe Bilimsel Yaklaşımlar [Remembering Life: Scientific Approaches to Autobiographical Memory] (pp. 185-200). Istanbul, Turkey: Koç University Press.
  • Mani, N., Mishra, R. K., & Huettig, F. (2018). Introduction to 'The Interactive Mind: Language, Vision and Attention'. In N. Mani, R. K. Mishra, & F. Huettig (Eds.), The Interactive Mind: Language, Vision and Attention (pp. 1-2). Chennai: Macmillan Publishers India.
  • McQueen, J. M., & Cutler, A. (1992). Words within words: Lexical statistics and lexical access. In J. Ohala, T. Neary, & B. Derwing (Eds.), Proceedings of the Second International Conference on Spoken Language Processing: Vol. 1 (pp. 221-224). Alberta: University of Alberta.

    Abstract

    This paper presents lexical statistics on the pattern of occurrence of words embedded in other words. We report the results of an analysis of 25000 words, varying in length from two to six syllables, extracted from a phonetically-coded English dictionary (The Longman Dictionary of Contemporary English). Each syllable, and each string of syllables within each word was checked against the dictionary. Two analyses are presented: the first used a complete list of polysyllables, with look-up on the entire dictionary; the second used a sublist of content words, counting only embedded words which were themselves content words. The results have important implications for models of human speech recognition. The efficiency of these models depends, in different ways, on the number and location of words within words.
  • 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.
  • Mitterer, H., Brouwer, S., & Huettig, F. (2018). How important is prediction for understanding spontaneous speech? In N. Mani, R. K. Mishra, & F. Huettig (Eds.), The Interactive Mind: Language, Vision and Attention (pp. 26-40). Chennai: Macmillan Publishers India.
  • 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.
  • Norcliffe, E. (2018). Egophoricity and evidentiality in Guambiano (Nam Trik). In S. Floyd, E. Norcliffe, & L. San Roque (Eds.), Egophoricity (pp. 305-345). Amsterdam: Benjamins.

    Abstract

    Egophoric verbal marking is a typological feature common to Barbacoan languages, but otherwise unknown in the Andean sphere. The verbal systems of three out of the four living Barbacoan languages, Cha’palaa, Tsafiki and Awa Pit, have previously been shown to express egophoric contrasts. The status of Guambiano has, however, remained uncertain. In this chapter, I show that there are in fact two layers of egophoric or egophoric-like marking visible in Guambiano’s grammar. Guambiano patterns with certain other (non-Barbacoan) languages in having ego-categories which function within a broader evidential system. It is additionally possible to detect what is possibly a more archaic layer of egophoric marking in Guambiano’s verbal system. This marking may be inherited from a common Barbacoan system, thus pointing to a potential genealogical basis for the egophoric patterning common to these languages. The multiple formal expressions of egophoricity apparent both within and across the four languages reveal how egophoric contrasts are susceptible to structural renewal, suggesting a pan-Barbacoan preoccupation with the linguistic encoding of self-knowledge.
  • Norris, D., Van Ooijen, B., & Cutler, A. (1992). Speeded detection of vowels and steady-state consonants. In J. Ohala, T. Neary, & B. Derwing (Eds.), Proceedings of the Second International Conference on Spoken Language Processing; Vol. 2 (pp. 1055-1058). Alberta: University of Alberta.

    Abstract

    We report two experiments in which vowels and steady-state consonants served as targets in a speeded detection task. In the first experiment, two vowels were compared with one voiced and once unvoiced fricative. Response times (RTs) to the vowels were longer than to the fricatives. The error rate was higher for the consonants. Consonants in word-final position produced the shortest RTs, For the vowels, RT correlated negatively with target duration. In the second experiment, the same two vowel targets were compared with two nasals. This time there was no significant difference in RTs, but the error rate was still significantly higher for the consonants. Error rate and length correlated negatively for the vowels only. We conclude that RT differences between phonemes are independent of vocalic or consonantal status. Instead, we argue that the process of phoneme detection reflects more finely grained differences in acoustic/articulatory structure within the phonemic repertoire.
  • Ozyurek, A. (2018). Cross-linguistic variation in children’s multimodal utterances. In M. Hickmann, E. Veneziano, & H. Jisa (Eds.), Sources of variation in first language acquisition: Languages, contexts, and learners (pp. 123-138). Amsterdam: Benjamins.

    Abstract

    Our ability to use language is multimodal and requires tight coordination between what is expressed in speech and in gesture, such as pointing or iconic gestures that convey semantic, syntactic and pragmatic information related to speakers’ messages. Interestingly, what is expressed in gesture and how it is coordinated with speech differs in speakers of different languages. This paper discusses recent findings on the development of children’s multimodal expressions taking cross-linguistic variation into account. Although some aspects of speech-gesture development show language-specificity from an early age, it might still take children until nine years of age to exhibit fully adult patterns of cross-linguistic variation. These findings reveal insights about how children coordinate different levels of representations given that their development is constrained by patterns that are specific to their languages.
  • Ozyurek, A. (2018). Role of gesture in language processing: Toward a unified account for production and comprehension. In S.-A. Rueschemeyer, & M. G. Gaskell (Eds.), Oxford Handbook of Psycholinguistics (2nd ed., pp. 592-607). Oxford: Oxford University Press. doi:10.1093/oxfordhb/9780198786825.013.25.

    Abstract

    Use of language in face-to-face context is multimodal. Production and perception of speech take place in the context of visual articulators such as lips, face, or hand gestures which convey relevant information to what is expressed in speech at different levels of language. While lips convey information at the phonological level, gestures contribute to semantic, pragmatic, and syntactic information, as well as to discourse cohesion. This chapter overviews recent findings showing that speech and gesture (e.g. a drinking gesture as someone says, “Would you like a drink?”) interact during production and comprehension of language at the behavioral, cognitive, and neural levels. Implications of these findings for current psycholinguistic theories and how they can be expanded to consider the multimodal context of language processing are discussed.
  • Pawley, A., & Hammarström, H. (2018). The Trans New Guinea family. In B. Palmer (Ed.), Papuan Languages and Linguistics (pp. 21-196). Berlin: De Gruyter Mouton.
  • Perdue, C., & Klein, W. (1992). Conclusions. In W. Klein, & C. Perdue (Eds.), Utterance structure: Developing grammars again (pp. 301-337). Amsterdam: Benjamins.
  • Perdue, C., & Klein, W. (1992). Introduction. In W. Klein, & C. Perdue (Eds.), Utterance structure: Developing grammars again (pp. 1-10). Amsterdam: Benjamins.
  • Piepers, J., & Redl, T. (2018). Gender-mismatching pronouns in context: The interpretation of possessive pronouns in Dutch and Limburgian. In B. Le Bruyn, & J. Berns (Eds.), Linguistics in the Netherlands 2018 (pp. 97-110). Amsterdam: Benjamins.

    Abstract

    Gender-(mis)matching pronouns have been studied extensively in experiments. However, a phenomenon common to various languages has thus far been overlooked: the systemic use of non-feminine pronouns when referring to female individuals. The present study is the first to provide experimental insights into the interpretation of such a pronoun: Limburgian zien ‘his/its’ and Dutch zijn ‘his/its’ are grammatically ambiguous between masculine and neuter, but while Limburgian zien can refer to women, the Dutch equivalent zijn cannot. Employing an acceptability judgment task, we presented speakers of Limburgian (N = 51) with recordings of sentences in Limburgian featuring zien, and speakers of Dutch (N = 52) with Dutch translations of these sentences featuring zijn. All sentences featured a potential male or female antecedent embedded in a stereotypically male or female context. We found that ratings were higher for sentences in which the pronoun could refer back to the antecedent. For Limburgians, this extended to sentences mentioning female individuals. Context further modulated sentence appreciation. Possible mechanisms regarding the interpretation of zien as coreferential with a female individual will be discussed.
  • 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.
  • Rommers, J., & Federmeier, K. D. (2018). Electrophysiological methods. In A. M. B. De Groot, & P. Hagoort (Eds.), Research methods in psycholinguistics and the neurobiology of language: A practical guide (pp. 247-265). Hoboken: Wiley.
  • 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.
  • San Roque, L. (2018). Egophoric patterns in Duna verbal morphology. In S. Floyd, E. Norcliffe, & L. San Roque (Eds.), Egophoricity (pp. 405-436). Amsterdam: Benjamins.

    Abstract

    In the language Duna (Trans New Guinea), egophoric distributional patterns are a pervasive characteristic of verbal morphology, but do not comprise a single coherent system. Many morphemes, including evidential markers and future time inflections, show strong tendencies to co-occur with ‘informant’ subjects (the speaker in a declarative, the addressee in an interrogative), or alternatively with non-informant subjects. The person sensitivity of the Duna forms is observable in frequency, speaker judgments of sayability, and subject implicatures. Egophoric and non-egophoric distributional patterns are motivated by the individual semantics of the morphemes, their perspective-taking properties, and logical and/or conventionalised expectations of how people experience and talk about events. Distributional tendencies can also be flouted, providing a resource for speakers to convey attitudes towards their own knowledge and experiences, or the knowledge and experiences of others.
  • San Roque, L., Floyd, S., & Norcliffe, E. (2018). Egophoricity: An introduction. In S. Floyd, E. Norcliffe, & L. San Roque (Eds.), Egophoricity (pp. 1-78). Amsterdam: Benjamins.
  • San Roque, L., & Schieffelin, B. B. (2018). Learning how to know. In S. Floyd, E. Norcliffe, & L. San Roque (Eds.), Egophoricity (pp. 437-471). Amsterdam: Benjamins. doi:10.1075/tsl.118.14san.

    Abstract

    Languages with egophoric systems require their users to pay special attention to who knows what in the speech situation, providing formal marking of whether the speaker or addressee has personal knowledge of the event being discussed. Such systems have only recently come to be studied in cross-linguistic perspective. This chapter has two aims in regard to contributing to our understanding of egophoric marking. Firstly, it presents relevant data from a relatively under-described and endangered language, Kaluli (aka Bosavi), spoken in Papua New Guinea. Unusually, Kaluli tense inflections appear to show a mix of both egophoric and first vs non-first person-marking features, as well as other contrasts that are broadly relevant to a typology of egophoricity, such as special constructions for the expression of involuntary experience. Secondly, the chapter makes a preliminary foray into issues concerning egophoric marking and child language, drawing on a naturalistic corpus of child-caregiver interactions. Questions for future investigation raised by the Kaluli data concern, for example, the potentially challenging nature of mastering inflections that are sensitive to both person and speech act type, the possible role of question-answer pairs in children’s acquisition of egophoric morphology, and whether there are special features of epistemic access and authority that relate particularly to child-adult interactions.
  • 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.

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