Intelligibility of normal speech I: Global and fine-grained acoustic-phonetic talker characteristics

Ann R. Bradlow*, Gina M. Torretta, David B. Pisoni

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

332 Scopus citations


This study used a multi-talker database containing intelligibility scores for 2000 sentences (20 talkers, 100 sentences), to identify talker-related correlates of speech intelligibility. We first investigated "global" talker characteristics (e.g., gender, F0 and speaking rate). Findings showed female talkers to be more intelligible as a group than male talkers. Additionally, we found a tendency for F0 range to correlate positively with higher speech intelligibility scores. However, F0 mean and speaking rate did not correlate with intelligibility. We then examined several fine-grained acoustic-phonetic talker-characteristics as correlates of overall intelligibility. We found that talkers with larger vowel spaces were generally more intelligible than talkers with reduced spaces. In investigating two cases of consistent listener errors (segment deletion and syllable affiliation), we found that these perceptual errors could be traced directly to detailed timing characteristics in the speech signal. Results suggest that a substantial portion of variability in normal speech intelligibility is traceable to specific acoustic-phonetic characteristics of the talker. Knowledge about these factors may be valuable for improving speech synthesis and recognition strategies, and for special populations (e.g., the hearing-impaired and second-language learners) who are particularly sensitive to intelligibility differences among talkers.

Original languageEnglish (US)
Pages (from-to)255-272
Number of pages18
JournalSpeech Communication
Issue number3-4
StatePublished - Dec 1996

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Communication
  • Language and Linguistics
  • Linguistics and Language
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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