Improvement and Assessment of Spectro-Temporal Modulation Analysis for Speech Intelligibility Estimation

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


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.


 DOI: 10.21437/Interspeech.2019-2898

Cite as: Edraki, A., Chan, W., Jensen, J., Fogerty, D. (2019) Improvement and Assessment of Spectro-Temporal Modulation Analysis for Speech Intelligibility Estimation. Proc. Interspeech 2019, 1378-1382, DOI: 10.21437/Interspeech.2019-2898.


@inproceedings{Edraki2019,
  author={Amin Edraki and Wai-Yip Chan and Jesper Jensen and Daniel Fogerty},
  title={{Improvement and Assessment of Spectro-Temporal Modulation Analysis for Speech Intelligibility Estimation}},
  year=2019,
  booktitle={Proc. Interspeech 2019},
  pages={1378--1382},
  doi={10.21437/Interspeech.2019-2898},
  url={http://dx.doi.org/10.21437/Interspeech.2019-2898}
}