Determining the relevance of different aspects of formant contours to intelligibility

Akiko Amano-Kusumoto, John Paul Hosom, Alexander Kain, Justin M. Aronoff

Research output: Contribution to journalArticle

3 Scopus citations


Previous studies have shown that "clear" speech, where the speaker intentionally tries to enunciate, has better intelligibility than "conversational" speech, which is produced in regular conversation. However, conversational and clear speech vary along a number of acoustic dimensions and it is unclear what aspects of clear speech lead to better intelligibility. Previously, Kain et al. (2008) showed that a combination of short-term spectra and duration was responsible for the improved intelligibility of one speaker. This study investigates subsets of specific features of short-term spectra including temporal aspects. Similar to Kain's study, hybrid stimuli were synthesized with a combination of features from clear speech and complementary features from conversational speech to determine which acoustic features cause the improved intelligibility of clear speech. Our results indicate that, although steady-state formant values of tense vowels contributed to the intelligibility of clear speech, neither the steady-state portion nor the formant transition was sufficient to yield comparable intelligibility to that of clear speech. In contrast, when the entire formant contour of conversational speech including the phoneme duration was replaced by that of clear speech, intelligibility was comparable to that of clear speech. It indicated that the combination of formant contour and duration information was relevant to the improved intelligibility of clear speech. The study provides a better understanding of the relevance of different aspects of formant contours to the improved intelligibility of clear speech.

Original languageEnglish (US)
Pages (from-to)1-9
Number of pages9
JournalSpeech Communication
StatePublished - Apr 1 2014



  • Speech intelligibility
  • Speech synthesis
  • Vowel perception

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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