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1
The Advantage of Knowing the Talker
Souza, Pamela [Sonstige]; Gehani, Namita [Sonstige]; Wright, Richard [Sonstige]. - 2020
DNB Subject Category Language
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2
cldf-datasets/phoible: PHOIBLE 2.0 as CLDF dataset ...
Moran, Steven; McCloy, Daniel. - : Zenodo, 2019
BASE
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3
Investigating the fit between phonological feature systems and brain responses to speech using EEG ...
McCloy, Daniel R.; Lee, Adrian K. C.. - : Taylor & Francis, 2019
BASE
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4
Investigating the fit between phonological feature systems and brain responses to speech using EEG ...
McCloy, Daniel R.; Lee, Adrian K. C.. - : Taylor & Francis, 2019
BASE
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5
Investigating the fit between phonological feature systems and brain responses to speech using EEG ...
McCloy, Daniel R.; Lee, Adrian K. C.. - : Taylor & Francis, 2019
BASE
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6
EEG-derived phoneme confusion matrices show the fit between phonological feature systems and brain responses to speech ...
McCloy, Daniel; Lee, Adrian. - : PsyArXiv, 2018
BASE
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7
Talker versus dialect effects on speech intelligibility: a symmetrical study
BASE
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8
Auditory attention strategy depends on target linguistic properties and spatial configurationa)
McCloy, Daniel R.; Lee, Adrian K. C.. - : Acoustical Society of America, 2015
BASE
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9
The Semantics of Implicitly Relational Predicates
BASE
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10
Prosody, intelligibility and familiarity in speech perception
BASE
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11
Separating segmental and prosodic contributions to intelligibility
Abstract: It is well known that the intelligibility of speech can vary both across individuals within styles or tasks, and within individuals across styles or tasks. Various properties of the speech signal have been shown to correlate with such differences in intelligibility, including speech rate, [5,7,8] segmental reduction or deletion, [1] vowel space size, [1,2,4,6] pitch range, [2] and pitch accent deletion. [3] However, these dimensions are rarely (if ever) manipulated independently in natural speech. This poses a challenge to understanding the sources of individual differences in intelligibility (both across individuals and across styles), and makes it difficult to know whether any particular dimension measured causes speech to be more or less intelligible, or merely indexes some other aspect of speech that is responsible for intelligibility differences. As an alternative to measuring fine-grained dimensions of the speech signal, this research makes a broad distinction between prosodic dimensions (pitch, intensity, and duration) on one hand, and segmental content on the other. Through careful resynthesis, a corpus of parallel sentences are created that effectively hold constant either prosody or segmental content across resynthesized “talkers”. High-quality stimuli are achieved by hand-correction of glottal pulse epochs and semi-automated hand segmentation of syllable durations, followed by automated dynamic time warping of durations and swapping of pitch and intensity contours. Results from a speech-in-noise task with both unmodified and resynthesized stimuli show that talkers with low intrinsic intelligibility may have relatively “good” prosody, evidenced by improvements in intelligibility when their prosody is mapped onto other talkers’ waveforms. In contrast, talkers with high intrinsic intelligibility may have relatively “bad” prosody, evidenced by lower intelligibility caused by mapping their prosody onto other talkers. A linear mixed-effects regression model (controlling for signal processing distortion and variation in sentence difficulty) supports this view: patterns of coefficients for “prosodic donor” and “segmental donor” show different rankings than the overall intelligibility scores for unmodified talkers. Comparison between these patterns and post-hoc acoustic analyses of the stimuli allows classification of acoustic predictors based on how well they correlate with “prosodic donor” or “segmental donor” coefficient patterns. References [1] Bond, Z. S., & Moore, T. J. (1994). A note on the acoustic-phonetic characteristics of inadvertently clear speech. Speech Communication, 14(4), 325–337. doi:10.1016/0167-6393(94)90026-4. [2] Bradlow, A. R., Torretta, G. M., & Pisoni, D. B. (1996). Intelligibility of normal speech I: Global and fine-grained acoustic-phonetic talker characteristics. Speech Communication, 20(3-4), 255–272. doi:10.1016/S0167-6393(96)00063-5. [3] Clopper, C. G., & Smiljanić, R. (2011). Effects of gender and regional dialect on prosodic patterns in American English. Journal of Phonetics, 39(2), 237–245. doi:10.1016/j.wocn.2011.02.006. [4] Hazan, V., & Markham, D. (2004). Acoustic-phonetic correlates of talker intelligibility for adults and children. The Journal of the Acoustical Society of America, 116(5), 3108–3118. doi:10.1121/1.1806826. [5] Mayo, C., Aubanel, V., & Cooke, M. (2012). Effect of prosodic changes on speech intelligibility. Paper presented at the 13th Annual Conference of the International Speech Communication Association. In INTERSPEECH-2012. url: http://interspeech2012.org/accepted-abstract.html?id=661 [6] Neel, A. T. (2008). Vowel space characteristics and vowel identification accuracy. Journal of Speech, Language, and Hearing Research, 51(3), 574–585. doi:10.1044/1092-4388(2008/041). [7] Sommers, M. S., Nygaard, L. C., & Pisoni, D. B. (1994). Stimulus variability and spoken word recognition I: Effects of variability in speaking rate and overall amplitude. The Journal of the Acoustical Society of America, 96(3), 1314–1324. doi:10.1121/1.411453. [8] Tolhurst, G. C. (1957). Effects of duration and articulation changes on intelligibility, word reception and listener preference. Journal of Speech and Hearing Disorders, 22(3), 328–334.
Keyword: intelligibility; linguistics; phonetics; prosody
URL: http://hdl.handle.net/1773/25274
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12
Corpus-based productivity measures of English -er agentives and instrumentals
McCloy, Daniel Robert. - : University of Washington, 2013
BASE
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13
Revisiting population size vs. phoneme inventory size
In: Language. - Washington, DC : Linguistic Society of America 88 (2012) 4, 877-893
BLLDB
OLC Linguistik
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14
Revisiting the Population vs Phoneme-inventory Correlation
In: Moran, Steven; McCloy, Daniel; Wright, Richard (2012). Revisiting the Population vs Phoneme-inventory Correlation. In: LSA Annual Meeting Extended Abstracts 2012. eLanguage, Portland, Oregon, 5 January 2012 - 8 January 2012. (2012)
BASE
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15
Modelling talker intelligibility variation in a dialect-controlled corpus
BASE
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16
Revisiting population size vs. phoneme inventory size
Moran, Steven; McCloy, Daniel Robert; Wright, Richard A.. - : Linguistic Society of America, 2012
BASE
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17
Revisiting the population vs phoneme-inventory correlation
In: LSA Annual Meeting Extended Abstracts; Vol 3: LSA Annual Meeting Extended Abstracts 2012; 29:1-5 ; 2377-3367 (2012)
BASE
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18
Vowel laxing in Indonesian as a test case for interaction of morphological and syllabic structure
BASE
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19
The semantics of implicitly relational predicates
McCloy, Daniel Robert. - : Simon Fraser University, 2010
BASE
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20
Automated Adaptation Between Kiranti Languages
McCloy, Daniel Richard. - : University of Montana, 2006
In: Graduate Student Theses, Dissertations, & Professional Papers (2006)
BASE
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