Evaluating a distortion-weighted glimpsing metric for predicting binaural speech intelligibility in rooms

Yan Tang, Richard J. Hughes, Bruno M. Fazenda, Trevor J. Cox

Research output: Contribution to journalArticlepeer-review


A distortion-weighted glimpse proportion metric (BiDWGP) for predicting binaural speech intelligibility were evaluated in simulated anechoic and reverberant conditions, with and without a noise masker. The predictive performance of BiDWGP was compared to four reference binaural intelligibility metrics, which were extended from the Speech Intelligibility Index (SII) and the Speech Transmission Index (STI). In the anechoic sound field, BiDWGP demonstrated high accuracy in predicting binaural intelligibility for individual maskers (ρ ≥ 0.95) and across maskers (ρ ≥ 0.94). The reference metrics however performed less well in across-masker prediction (0.54 ≤ ρ ≤ 0.86) despite reasonable accuracy for individual maskers. In reverberant rooms, BiDWGP was more stable in all test conditions (ρ ≥ 0.87) than the reference metrics, which showed different predictive patterns: the binaural STIs were more robust for the stationary than for the fluctuating noise masker, whilst the binaural SII displayed the opposite behaviour. The study shows that the new BiDWGP metric can provide similar or even more robust predictive power than the current standard metrics.

Original languageEnglish (US)
Pages (from-to)26-37
Number of pages12
JournalSpeech Communication
StatePublished - Sep 1 2016
Externally publishedYes


  • Binaural
  • Glimpsing
  • Noise
  • Objective intelligibility metric
  • Reverberation
  • Speech

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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