Publications

Displaying 1 - 22 of 22
  • Becker, A., & Klein, W. (1984). Notes on the internal organization of a learner variety. In P. Auer, & A. Di Luzio (Eds.), Interpretive sociolinguistics (pp. 215-231). Tübingen: Narr.
  • 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.
  • 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. (1984). Stress and accent in language production and understanding. In D. Gibbon, & H. Richter (Eds.), Intonation, accent and rhythm: Studies in discourse phonology (pp. 77-90). Berlin: de Gruyter.
  • Cutler, A., & Clifton, Jr., C. (1984). The use of prosodic information in word recognition. In H. Bouma, & D. G. Bouwhuis (Eds.), Attention and performance X: Control of language processes (pp. 183-196). London: Erlbaum.

    Abstract

    In languages with variable stress placement, lexical stress patterns can convey information about word identity. The experiments reported here address the question of whether lexical stress information can be used in word recognition. The results allow the following conclusions: 1. Prior information as to the number of syllables and lexical stress patterns of words and nonwords does not facilitate lexical decision responses (Experiment 1). 2. The strong correspondences between grammatical category membership and stress pattern in bisyllabic English words (strong-weak stress being associated primarily with nouns, weak-strong with verbs) are not exploited in the recognition of isolated words (Experiment 2). 3. When a change in lexical stress also involves a change in vowel quality, i.e., a segmental as well as a suprasegmental alteration, effects on word recognition are greater when no segmental correlates of suprasegmental changes are involved (Experiments 2 and 3). 4. Despite the above finding, when all other factors are controlled, lexical stress information per se can indeed be shown to play a part in word-recognition process (Experiment 3).
  • Cutler, A., & Clifton Jr., C. (1984). The use of prosodic information in word recognition. In H. Bouma, & D. Bouwhuis (Eds.), Attention and Performance X: Control of Language Processes (pp. 183-196). Hillsdale, NJ: Erlbaum.
  • 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.
  • Klein, W. (1984). Bühler Ellipse. In C. F. Graumann, & T. Herrmann (Eds.), Karl Bühlers Axiomatik: Fünfzig Jahre Axiomatik der Sprachwissenschaften (pp. 117-141). Frankfurt am Main: Klostermann.
  • Klein, W. (1967). Einführende Bibliographie zu "Mathematik und Dichtung". In H. Kreuzer, & R. Gunzenhäuser (Eds.), Mathematik und Dichtung (pp. 347-359). München: Nymphenburger.
  • Levelt, W. J. M. (1984). Geesteswetenschappelijke theorie als kompas voor de gangbare mening. In S. Dresden, & D. Van de Kaa (Eds.), Wetenschap ten goede en ten kwade (pp. 42-52). Amsterdam: North Holland.
  • 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. (1984). Spontaneous self-repairs in speech: Processes and representations. In M. P. R. Van den Broecke, & A. Cohen (Eds.), Proceedings of the 10th International Congress of Phonetic Sciences (pp. 105-117). Dordrecht: Foris.
  • Levelt, W. J. M. (1984). Some perceptual limitations on talking about space. In A. J. Van Doorn, W. A. Van de Grind, & J. J. Koenderink (Eds.), Limits in perception (pp. 323-358). Utrecht: VNU Science 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.
  • 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.
  • Nas, G., Kempen, G., & Hudson, P. (1984). De rol van spelling en klank bij woordherkenning tijdens het lezen. In A. Thomassen, L. Noordman, & P. Elling (Eds.), Het leesproces. Lisse: Swets & Zeitlinger.
  • Rossi, G. (2021). Conversation analysis (CA). In J. Stanlaw (Ed.), The International Encyclopedia of Linguistic Anthropology. Wiley-Blackwell. doi:10.1002/9781118786093.iela0080.

    Abstract

    Conversation analysis (CA) is an approach to the study of language and social interaction that puts at center stage its sequential development. The chain of initiating and responding actions that characterizes any interaction is a source of internal evidence for the meaning of social behavior as it exposes the understandings that participants themselves give of what one another is doing. Such an analysis requires the close and repeated inspection of audio and video recordings of naturally occurring interaction, supported by transcripts and other forms of annotation. Distributional regularities are complemented by a demonstration of participants' orientation to deviant behavior. CA has long maintained a constructive dialogue and reciprocal influence with linguistic anthropology. This includes a recent convergence on the cross-linguistic and cross-cultural study of social interaction.
  • Seuren, P. A. M. (1984). Logic and truth-values in language. In F. Landman, & F. Veltman (Eds.), Varieties of formal semantics: Proceedings of the fourth Amsterdam colloquium (pp. 343-364). Dordrecht: Foris.
  • Weissenborn, J., & Stralka, R. (1984). Das Verstehen von Mißverständnissen. Eine ontogenetische Studie. In Zeitschrift für Literaturwissenschaft und Linguistik (pp. 113-134). Stuttgart: Metzler.
  • Weissenborn, J. (1984). La genèse de la référence spatiale en langue maternelle et en langue seconde: similarités et différences. In G. Extra, & M. Mittner (Eds.), Studies in second language acquisition by adult immigrants (pp. 262-286). Tilburg: Tilburg University.

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