Publications

Displaying 1 - 19 of 19
  • Bosker, H. R. (2021). The contribution of amplitude modulations in speech to perceived charisma. In B. Weiss, J. Trouvain, M. Barkat-Defradas, & J. J. Ohala (Eds.), Voice attractiveness: Prosody, phonology and phonetics (pp. 165-181). Singapore: Springer. doi:10.1007/978-981-15-6627-1_10.

    Abstract

    Speech contains pronounced amplitude modulations in the 1–9 Hz range, correlating with the syllabic rate of speech. Recent models of speech perception propose that this rhythmic nature of speech is central to speech recognition and has beneficial effects on language processing. Here, we investigated the contribution of amplitude modulations to the subjective impression listeners have of public speakers. The speech from US presidential candidates Hillary Clinton and Donald Trump in the three TV debates of 2016 was acoustically analyzed by means of modulation spectra. These indicated that Clinton’s speech had more pronounced amplitude modulations than Trump’s speech, particularly in the 1–9 Hz range. A subsequent perception experiment, with listeners rating the perceived charisma of (low-pass filtered versions of) Clinton’s and Trump’s speech, showed that more pronounced amplitude modulations (i.e., more ‘rhythmic’ speech) increased perceived charisma ratings. These outcomes highlight the important contribution of speech rhythm to charisma perception.
  • Bowerman, M. (1977). The acquisition of word meaning: An investigation of some current concepts. In P. Johnson Laird, & P. Wason (Eds.), Thinking: Readings in cognitive science (pp. 239-253). Cambridge: Cambridge University Press.
  • Coopmans, C. W., De Hoop, H., Kaushik, K., Hagoort, P., & Martin, A. E. (2021). Structure-(in)dependent interpretation of phrases in humans and LSTMs. In Proceedings of the Society for Computation in Linguistics (SCiL 2021) (pp. 459-463).

    Abstract

    In this study, we compared the performance of a long short-term memory (LSTM) neural network to the behavior of human participants on a language task that requires hierarchically structured knowledge. We show that humans interpret ambiguous noun phrases, such as second blue ball, in line with their hierarchical constituent structure. LSTMs, instead, only do so after unambiguous training, and they do not systematically generalize to novel items. Overall, the results of our simulations indicate that a model can behave hierarchically without relying on hierarchical constituent structure.
  • Cutler, A. (1977). The context-dependence of "intonational meanings". In W. Beach, S. Fox, & S. Philosoph (Eds.), Papers from the Thirteenth Regional Meeting, Chicago Linguistic Society (pp. 104-115). Chicago, Ill.: CLS.
  • Cutler, A. (1977). The psychological reality of word formation and lexical stress rules. In E. Fischer-Jørgensen, J. Rischel, & N. Thorsen (Eds.), Proceedings of the Ninth International Congress of Phonetic Sciences: Vol. 2 (pp. 79-85). Copenhagen: Institute of Phonetics, University of Copenhagen.
  • Cutler, A., & Jesse, A. (2021). Word stress in speech perception. In J. S. Pardo, L. C. Nygaard, & D. B. Pisoni (Eds.), The handbook of speech perception (2nd ed., pp. 239-265). Chichester: Wiley.
  • Frost, R. L. A., & Casillas, M. (2021). Investigating statistical learning of nonadjacent dependencies: Running statistical learning tasks in non-WEIRD populations. In SAGE Research Methods Cases. doi:10.4135/9781529759181.

    Abstract

    Language acquisition is complex. However, one thing that has been suggested to help learning is the way that information is distributed throughout language; co-occurrences among particular items (e.g., syllables and words) have been shown to help learners discover the words that a language contains and figure out how those words are used. Humans’ ability to draw on this information—“statistical learning”—has been demonstrated across a broad range of studies. However, evidence from non-WEIRD (Western, Educated, Industrialized, Rich, and Democratic) societies is critically lacking, which limits theorizing on the universality of this skill. We extended work on statistical language learning to a new, non-WEIRD linguistic population: speakers of Yélî Dnye, who live on a remote island off mainland Papua New Guinea (Rossel Island). We performed a replication of an existing statistical learning study, training adults on an artificial language with statistically defined words, then examining what they had learnt using a two-alternative forced-choice test. Crucially, we implemented several key amendments to the original study to ensure the replication was suitable for remote field-site testing with speakers of Yélî Dnye. We made critical changes to the stimuli and materials (to test speakers of Yélî Dnye, rather than English), the instructions (we re-worked these significantly, and added practice tasks to optimize participants’ understanding), and the study format (shifting from a lab-based to a portable tablet-based setup). We discuss the requirement for acute sensitivity to linguistic, cultural, and environmental factors when adapting studies to test new populations.
  • Kempen, G. (1977). Building a psychologically plausible sentence generator. In P. A. M. Seuren (Ed.), Symposium on semantic theory: held at Nijmegen, March 14-18, 1977 / Volume 9 (pp. 107-117 ). Nijmegen: Katholieke Universiteit Nijmegen.

    Abstract

    The psychological process of translating semantic into syntactic structures has dynamic properties such as the following. (1) The speaker is able to start pronouncing an utterance before having worked out the semantic content he wishes to express. Selection of semantic content and construction of syntactic form proceed partially in parallel. (2) The human sentence generator takes as input not only a specification of semantic content but also some indication of desired syntactic shape. Such indications, if present, do not complicate the generation process but make it easier. (3) Certain regularities of speech errors suggest a two-stage generation process. Stage I constructs the “syntactic skeleton” of an utterance; stage II provides the skeleton with morpho- honological information. An outline is given of the type of grammar which is used by a sentence generation system embodying these characteristics. The system is being implemented on a computer.
  • Kempen, G. (1977). Conceptualizing and formulating in sentence production. In S. Rosenberg (Ed.), Sentence production: Developments in research and theory (pp. 259-274). Hillsdale, NJ: Erlbaum.
  • Kempen, G. (1977). Man's sentence generator: Aspects of its control structure. In M. De Mey, R. Pinxten, M. Poriau, & E. Vandamme (Eds.), International workshop on the cognitive viewpoint. Ghent: University of Ghent, Communication & Cognition.
  • Kempen, G., & Maassen, B. (1977). The time course of conceptualizing and formulating processes during the production of simple sentences. In Proceedings of The Third Prague Conference on the Psychology of Human Learning and Development. Prague: Institute of Psychology.

    Abstract

    The psychological process of producing sentences includes conceptualization (selecting to-beexpressed conceptual content) and formulation (translating conceptual content into syntactic structures of a language). There is ample evidence, both intuitive and experimental, that the conceptualizing and formulating processes often proceed concurrently, not strictly serially. James Lindsley (Cognitive Psych.,1975, 7, 1-19; J.Psycholinguistic Res., 1976, 5, 331-354) has developed a concurrent model which proved succesful in an experimental situation where simple English Subject-Verb (SV) sentences such as “The boy is greeting”,”The girl is kicking” were produced as descriptions of pictures which showed actor and action. The measurements were reaction times defined as the interval between the moment a picture appeared on a screen and the onset of the vocal utterance by the speaker. Lindsley could show, among other things, that the formulation process for an SV sentence doesn’t start immediately after the actor of a picture (that is, the conceptual content underlying the surface Subject phrase) has been identified, but is somewhat delayed. The delay was needed, according to Lindsley, in order to prevent dysfluencies (hesitations) between surface Subject and verb. We replicated Lindsley’s data for Dutch. However, his model proved inadequate when we added Dutch Verb-Subject (VS) constructions which are obligatory in certain syntactic contexts but synonymous with their SV counterparts. A sentence production theory which is being developed by the first author is able to provide an accurate account of the data. The abovementioned delay is attributed to certain precautions the sentence generator has to take in case of SV but not of VS sentences. These precautions are related to the goal of attaining syntactic coherence of the utterance as a whole, not to the prevention of dysfluencies.
  • Kempen, G. (1977). Wat is psycholinguistiek? In B. T. M. Tervoort (Ed.), Wetenschap en taal: Het verschijnsel taal van verschillende zijden benaderd (pp. 86-99 ). Muiderberg: Coutinho.
  • Klein, W. (1977). Die Wissenschaft der Interpretation. In W. Klein (Ed.), Methoden der Textanalyse (pp. 1-23). Heidelberg: Quelle und Meyer.
  • Klein, W. (1977). Transitional grammars in the acquisition of German by Spanish and Italian workers. In J. Meisel (Ed.), Langues en contact - Pidgins - Creoles - Languages in contact (pp. 167-183). Tübingen: Narr.
  • Levelt, W. J. M., Van Gent, J., Haans, A., & Meijers, A. (1977). Grammaticality, paraphrase, and imagery. In S. Greenbaum (Ed.), Acceptability in language (pp. 87-101). The Hague: Mouton.
  • 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. (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, 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.
  • Levshina, N. (2021). Conditional inference trees and random forests. In M. Paquot, & T. Gries (Eds.), Practical Handbook of Corpus Linguistics (pp. 611-643). New York: Springer.

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