Title: A multi-channel speech enhancement framework for robust NMF-based speech recognition for speech-impaired users
Authors: Dekkers, Gert
van Waterschoot, Toon
Vanrumste, Bart
Van Den Broeck, Bert
Gemmeke, Jort
Van hamme, Hugo
Karsmakers, Peter
Issue Date: 6-Sep-2015
Publisher: ISCA
Host Document: INTERSPEECH 2015: proceedings pages:746-750
Conference: INTERSPEECH 2015 edition:16 location:Dresden, Germany date:6-10 September 2015
Article number: 1506
Abstract: 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.
Description: 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.
Publication status: published
KU Leuven publication type: IC
Appears in Collections:Electrical Engineering (ESAT) TC, Technology Campus Geel
Technologiecluster ESAT Elektrotechnische Engineering
ESAT - PSI, Processing Speech and Images

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