INTERSPEECH 2015 edition:16 location:Dresden, Germany date:6-10 September 2015
In this paper a multi-channel speech enhancement framework for distant speech acquisition in noisy and reverberant environments for Non-negative Matrix Factorization (NMF)-based Automatic Speech Recognition (ASR) is proposed. The system is evaluated for its use in an assistive vocal interface for physically impaired and speech-impaired users. The framework utilises the Spatially Pre-processed Speech Distortion Weighted Multi-channel Wiener Filter (SP-SDW-MWF) in combination with a postfilter to reduce noise and reverberation. Additionally, the estimation uncertainty of the speech enhancement framework is propagated through the Mel-Frequency Cepstrum Coefficients (MFCC) feature extraction to allow for feature compensation in a later stage. Results indicate that a) using a trade-off parameter between noise reduction and speech distortion has a positive effect on the recognition performance with respect to the well-known GSC and MWF and b) the addition of a postfilter and the feature compensation increases performance with respect to several baselines for a non-pathological and pathological speaker.
Dekkers G., van Waterschoot T., Vanrumste B., Van Den Broeck B., Gemmeke J.F., Van hamme H., Karsmakers P., ''A multi-channel speech enhancement framework for robust NMF-based speech recognition for speech-impaired users'', Proceedings 16th annual conference of the International Speech Communication Association (ISCA) - Interspeech 2015, pp. 746-750, September 6-10, 2015, Dresden, Germany.