Multiple levels of linguistic and paralinguistic features contribute to voice recognition

Jean Mary Zarate, Xing Tian, Kevin J P Woods, David Poeppel

Research output: Contribution to journalArticle

Abstract

Voice or speaker recognition is critical in a wide variety of social contexts. In this study, we investigated the contributions of acoustic, phonological, lexical, and semantic information toward voice recognition. Native English speaking participants were trained to recognize five speakers in five conditions: non-speech, Mandarin, German, pseudo-English, and English. We showed that voice recognition significantly improved as more information became available, from purely acoustic features in non-speech to additional phonological information varying in familiarity. Moreover, we found that the recognition performance is transferable between training and testing in phonologically familiar conditions (German, pseudo-English, and English), but not in unfamiliar (Mandarin) or non-speech conditions. These results provide evidence suggesting that bottom-up acoustic analysis and top-down influence from phonological processing collaboratively govern voice recognition.

Original languageEnglish (US)
Article number11475
JournalScientific reports
Volume5
DOIs
StatePublished - Jun 19 2015

ASJC Scopus subject areas

  • General

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