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Laboratory Phonology

Journal of the Association for Laboratory Phonology

Ed. by Cole, Jennifer


IMPACT FACTOR 2015: 0.667
Rank 85 out of 179 in category Linguistics in the 2015 Thomson Reuters Journal Citation Report/Social Sciences Edition

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1868-6354
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Signal-based and expectation-based factors in the perception of prosodic prominence

Jennifer Cole / Yoonsook Mo / Mark Hasegawa-Johnson
Published Online: 2010-11-04 | DOI: https://doi.org/10.1515/labphon.2010.022

Abstract

The perception of prosodic prominence in spontaneous speech is investigated through an online task of prosody transcription using untrained listeners. Prominence is indexed through a probabilistic prominence score assigned to each word based on the proportion of transcribers who perceived the word as prominent. Correlation and regression analyses between perceived prominence, acoustic measures and measures of a word's information status are conducted to test three hypotheses: (i) prominence perception is signal-driven, influenced by acoustic factors reflecting speakers' productions; (ii) perception is expectation-driven, influenced by the listener's prior experience of word frequency and repetition; (iii) any observed influence of word frequency on perceived prominence is mediated through the acoustic signal. Results show correlates of perceived prominence in acoustic measures, in word log-frequency and in the repetition index of a word, consistent with both signal-driven and expectation-driven hypotheses of prominence perception. But the acoustic correlates of perceived prominence differ somewhat from the correlates of word frequency, suggesting an independent effect of frequency on prominence perception. A speech processing account is offered as a model of signal-driven and expectation-driven effects on prominence perception, where prominence ratings are a function of the ease of lexical processing, as measured through the activation levels of lexical and sub-lexical units.

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Published Online: 2010-11-04

Published in Print: 2010-10-01


Citation Information: Laboratory Phonology, Volume 1, Issue 2, Pages 425–452, ISSN (Online) 1868-6354, ISSN (Print) 1868-6346, DOI: https://doi.org/10.1515/labphon.2010.022.

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© 2010 Walter de Gruyter GmbH & Co. KG, Berlin/New York. Copyright Clearance Center

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[1]
Joseph Roy, Jennifer Cole, and Timothy Mahrt
Laboratory Phonology: Journal of the Association for Laboratory Phonology, 2017, Volume 8, Number 1, Page 22
[2]
Yi Ting Huang, Rochelle S. Newman, Allison Catalano, and Matthew J. Goupell
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[3]
Kiwako Ito, Rory Turnbull, and Shari R. Speer
Laboratory Phonology, 2017, Volume 8, Number 1
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Jennifer Cole, Timothy Mahrt, and Joseph Roy
Computer Speech & Language, 2017, Volume 45, Page 300
[6]
Rory Turnbull, Adam J. Royer, Kiwako Ito, and Shari R. Speer
Language, Cognition and Neuroscience, 2017, Volume 32, Number 8, Page 1017
[7]
Antti Suni, Juraj Šimko, Daniel Aalto, and Martti Vainio
Computer Speech & Language, 2017, Volume 45, Page 123
[8]
Jennifer Cole and Stefanie Shattuck-Hufnagel
Laboratory Phonology, 2016, Volume 7, Number 1, Page 8
[9]
Sofoklis Kakouros and Okko Räsänen
Speech Communication, 2016, Volume 82, Page 67
[10]
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[11]
David Escudero-Mancebo, César González-Ferreras, Carlos Vivaracho-Pascual, and Valentín Cardeñoso-Payo
Computer Speech & Language, 2014, Volume 28, Number 1, Page 326
[12]
Jennifer Cole
Language, Cognition and Neuroscience, 2015, Volume 30, Number 1-2, Page 1
[13]
Scott H. Fraundorf, Duane G. Watson, and Aaron S. Benjamin
Language, Cognition and Neuroscience, 2015, Volume 30, Number 5, Page 606
[14]
[15]
Anne Lacheret, Anne Catherine Simon, Jean-Philippe Goldman, and Mathieu Avanzi
Language Sciences, 2013, Volume 39, Page 95

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