Language redundancy predicts syllabic duration and the spectral characteristics of vocalic syllable nuclei

Matthew Aylett, Alice Turk

Research output: Contribution to journalArticlepeer-review

161 Citations (Scopus)

Abstract

The language redundancy of a syllable, measured by its predictability given its context and inherent frequency, has been shown to have a strong inverse relationship with syllabic duration. This relationship is predicted by the smooth signal redundancy hypothesis, which proposes that robust communication in a noisy environment can be achieved with an inverse relationship between language redundancy and the predictability given acoustic observations (acoustic redundancy). A general version of the hypothesis predicts similar relationships between the spectral characteristics of speech and language redundancy. However, investigating this claim is hampered by difficulties in measuring the spectral characteristics of speech within large conversational corpora, and difficulties in forming models of acoustic redundancy based on these spectral characteristics. This paper addresses these difficulties by testing the smooth signal redundancy hypothesis with a very high-quality corpus collected for speech synthesis, and presents both durational and spectral data from vowel nuclei on a vowel-by-vowel basis. Results confirm the duration/ language redundancy results achieved in previous work, and show a significant relationship between language redundancy factors and the first two formants, although these results vary considerably by vowel. In general, however, vowels show increased centralization with increased language redundancy.
Original languageEnglish
Pages (from-to)3048-58
Number of pages11
JournalJournal of the Acoustical Society of America
Volume119
Issue number5
DOIs
Publication statusPublished - 1 May 2006

Keywords

  • Communication
  • Female
  • Humans
  • Language
  • Linear Models
  • Male
  • Models, Biological
  • Speech Acoustics
  • Speech Production Measurement
  • Time Factors
  • Speech Communication
  • Phonetics
  • HUman Voice
  • Acoustics
  • Speech Perception
  • Speech Processing Systems
  • Speech Synthesis
  • Vowel Systems
  • Regression Analysis
  • Statistical Analysis

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