Non-intrusive intelligibility prediction using a codebook-based approach. S⊘rensen, C., Kavalekalam, M. S., Xenaki, A., Boldt, J. B., & Christensen, M. G. In 2017 25th European Signal Processing Conference (EUSIPCO), pages 216-220, Aug, 2017.
Non-intrusive intelligibility prediction using a codebook-based approach [pdf]Paper  doi  abstract   bibtex   
It could be beneficial for users of hearing aids if these were able to automatically adjust the processing according to the speech intelligibility in the specific acoustic environment. Most speech intelligibility metrics are intrusive, i.e., they require a clean reference signal, which is rarely available in real-life applications. This paper proposes a method, which allows using an intrusive short-time objective intelligibility (STOI) metric without requiring access to a clean signal. The clean speech reference signal is replaced by the clean speech envelope spectrum estimated from the noisy signal. The spectral envelope has been shown to be an important cue for speech intelligibility and is used as the reference signal inside STOI. The spectral envelopes are estimated as a combination of predefined dictionaries, i.e., code-books, that best fits the noisy speech signal. The simulations show a high correlation between the proposed non-intrusive codebook-based STOI (NIC-STOI) and the intrusive STOI indicating that NIC-STOI is a suitable metric for automatic classification of speech signals.

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