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       Demo of speech dereverberation

- (2018.08)  Our paper "All-neural online source separation, counting, and diarization for meeting analysis'' was accepted for ICASSP-2019.  You can check out our demo to see how it works.

- (2017.08)  We gave a presentation at ICASSP-2018 about "Listening to each speaker one by one with reccurent selective hearing networks.'' It's a DNN framework to jointly perform source separation and source counting.

- (2017.08)  We gave a presentation at Interspeech-2017 about "Neural Network-Based Spectrum Estimation for Online WPE Dereverberation.'' It is an DNN-based extention of state-of-the-art speech dereverberation called weighted prediction error (WPE).

- (2017.03)  We gave a presentation at ICASSP-2017 about "Deep mixture density network for statistical model-based feature enhancement.''

- (2015.12)  We won the CHiME-3 challenge. See the CHiME-3 challenge webpage for mote details.

- (2014.05)  We organized REVERB challenge in collaboration with E. Habets, R. Haeb-Umbach, V. Leutnant, A. Sehr, W. Kellermann, R. Maas, S. Gannot and B. Raj. Many research institutes (including us, NTT) took part in the challenge to evaluate their own dereverberation algorithm and ASR technique based on a common evaluation database.
See the challenge webpage for mote details.

- (2011.09)  We won the CHiME-3 challenge. Demo sounds for denoising method (highly non-stationary noisy environment) presented at CHiME challenge were uploaded here.

- (2009.02)  Developed a commercial dereverberation software (Pro Tools plugin). Demo sounds and a demo version of the software are now available at this webpage.



Keisuke Kinoshita at lab.ntt.co.jp