Speech enhancement using beamforming and non negative matrix factorization for robust speech recognition in the CHiME-3 challenge
2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU)(2015)
摘要
In this paper we present our contribution to the third CHiME challenge on speech separation and recognition for noisy multi-channel recordings. The use-case of the challenge consists in single speaker utterances recorded in highly non-stationary noisy environments using a 6-microphone array mounted on a tablet computer. The front-end of our system is performing speech enhancement by cascading a cross-correlation-based channel selection, Signal Dependent MVDR beamforming and online source separation based on sparse NMF. The back-end module is a state-of-the-art speech recognition system with DNN acoustic models trained on fMLLR features and a RNN Language Model. Our system reaches an overall WER of 11.94% on real test recordings, achieving a relative improvement of 65% compared to the baseline system.
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关键词
Speech Enhancement,Automatic Speech Recognition,MVDR Beamforming,Non Negative Matrix Factorization,CHiME challenge
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