@inproceedings{2d87dc56e754423fafb4f3e993edc4be,
title = "Improvement and Assessment of Spectro-Temporal Modulation Analysis for Speech Intelligibility Estimation",
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.",
keywords = "Spectro-temporal modulation, Speech intelligibility, Speech quality model",
author = "Amin Edraki and Chan, {Wai Yip Geoffrey} and Jesper Jensen and Daniel Fogerty",
year = "2019",
month = sep,
doi = "10.21437/Interspeech.2019-2898",
language = "English",
volume = "2019-September",
series = "Proceedings of the International Conference on Spoken Language Processing",
publisher = "ISCA",
pages = "1378--1382",
booktitle = "Interspeech 2019",
note = "Interspeech 2019 ; Conference date: 15-09-2019 Through 19-09-2019",
}