期刊
COGNITION
卷 108, 期 3, 页码 804-809出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.cognition.2008.04.004
关键词
Speech perception; Word recognition; Ideal observer model; Categorization
资金
- NICHD NIH HHS [R01 HD073890] Funding Source: Medline
- NIDCD NIH HHS [DC-005071, R01 DC005071, R01 DC005071-07] Funding Source: Medline
Listeners are exquisitely sensitive to fine-grained acoustic detail within phonetic categories for sounds and words. Here we show that this sensitivity is optimal given the probabilistic nature of speech cues. We manipulated the probability distribution of one probabilistic cue, voice onset time (VOT), which differentiates word initial labial stops in English (e.g., beach and peach). Participants categorized words from distributions of VOT with wide or narrow variances. Uncertainty about word identity was measured by four-alternative forced-choice judgments and by the probability of looks to pictures. Both measures closely reflected the posterior probability of the word given the likelihood distributions of VOT, suggesting that listeners are sensitive to these distributions. (C) 2008 Elsevier B.V. All rights reserved.
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