Improvement and assessment of spectro-temporal modulation analysis for speech intelligibility estimation

Amin Edraki, Wai Yip Chan, Jesper Jensen, Daniel Fogerty

Research output: Contribution to journalConference articlepeer-review

Abstract

Several recent high-performing intelligibility estimators of acoustically degraded speech signals employ temporal modulation analysis. In this paper, we investigate the utility of using both spectro- and temporal-modulation for estimating speech intelligibility. We modified a pre-existing speech intelligibility estimation scheme (STMI) that was inspired by human auditory spectro-temporal modulation analysis. We produced several variants of the modified STMI and assessed their intelligibility prediction accuracy, in comparison with several high-performing estimators. Among the estimators tested, one of the STMI variants and eSTOI performed consistently well on both noisy and reverberated speech. These results suggest that spectro-temporal modulation analysis is useful for certain degradation conditions such as modulated noise and reverberation.

Original languageEnglish (US)
Pages (from-to)1378-1382
Number of pages5
JournalProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Volume2019-September
DOIs
StatePublished - 2019
Externally publishedYes
Event20th Annual Conference of the International Speech Communication Association: Crossroads of Speech and Language, INTERSPEECH 2019 - Graz, Austria
Duration: Sep 15 2019Sep 19 2019

Keywords

  • Spectro-temporal modulation
  • Speech intelligibility
  • Speech quality model

ASJC Scopus subject areas

  • Language and Linguistics
  • Human-Computer Interaction
  • Signal Processing
  • Software
  • Modeling and Simulation

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