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An Algorithm for Intelligibility Prediction of Time–Frequency Weighted Noisy Speech
Abstract
In the development process of noise-reduction algorithms, an objective machine-driven intelligibility measure which shows high correlation with speech intelligibility is of great interest. Besides reducing time and costs compared to real listening experiments, an objective intelligibility measure could also help provide answers on how to improve the intelligibility of noisy unprocessed speech. In this paper, a short-time objective intelligibility measure (STOI) is presented, which shows high correlation with the intelligibility of noisy and time-frequency weighted noisy speech (e.g., resulting from noise reduction) of three different listening experiments. In general, STOI showed better correlation with speech intelligibility compared to five other reference objective intelligibility models. In contrast to other conventional intelligibility models which tend to rely on global statistics across entire sentences, STOI is based on shorter time segments (386 ms). Experiments indeed show that it is beneficial to take segment lengths of this order into account. In addition, a free Matlab implementation is provided.
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Cited by
Real Time Speech Enhancement in the Waveform Domain
Défossez, A., Synnaeve, G., & Adi, Y. (2020) · Interspeech 2020 · doi:10.21437/interspeech.2020-2409 · Cited by 537
Tan, K., & Wang, D. (2020) · IEEE/ACM Transactions on Audio, Speech, and Language Processing · doi:10.1109/taslp.2019.2955276 · Cited by 348
Herff, C., Diener, L., Angrick, M., Mugler, E., Tate, M. C., Goldrick, M. A., Krusienski, D. J., Slutzky, M. W., & Schultz, T. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.01267 · Cited by 118
Angrick, M., Ottenhoff, M. C., Diener, L., Ivucic, D., Ivucic, G., Goulis, S., Saal, J., Colon, A. J., Wagner, L., Krusienski, D. J., et al. (2021) · Communications Biology · doi:10.1038/s42003-021-02578-0 · Cited by 125
Noise Estimation for Generative Diffusion Models
San-Roman, R., Nachmani, E., & Wolf, L. (2021) · arXiv · doi:10.48550/arxiv.2104.02600 · Cited by 44
Metadata
- Authors
- Taal, C. H., Hendriks, R. C., Heusdens, R., & Jensen, J.
- Venue
- IEEE Transactions on Audio, Speech, and Language Processing
- Published
- 2011-09
- Volume
- 19
- Issue
- 7
- Pages
- 2125-2136
- ISSN
- 1558-7916 (ISSN-L)
- 1558-7924
- OpenAlex
- W2141998673
- Cited by
- 2,254
- References
- 0
- FWCI
- 46.96
- Type
- journal article
- Language
- en
- Open access
- closed
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- Taal, C. H., Hendriks, R. C., Heusdens, R., & Jensen, J. (2011). An Algorithm for Intelligibility Prediction of Time–Frequency Weighted Noisy Speech. IEEE Transactions on Audio, Speech, and Language Processing. https://doi.org/10.1109/tasl.2011.2114881
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