Machine Listening in Multisource Environments (CHiME) 2011

Florence, Italy
September 1, 2011

Exemplar-Based Speech Enhancement and its Application to Noise-Robust Automatic Speech Recognition

Jort F. Gemmeke (1), Tuomas Virtanen (2), Antti Hurmalainen (2)

(1) Department ESAT, Katholieke Universiteit Leuven, Belgium
(2) Department of Signal Processing, Tampere University of Technology, Finland

In this work an exemplar-based technique for speech enhancement of noisy speech is proposed. The technique works by finding a sparse representation of the noisy speech in a dictionary containing both speech and noise exemplars, and uses the activated dictionary atoms to create a time-varying filter to enhance the noisy speech. The speech enhancement algorithm is evaluated using measured signal to noise ratio (SNR) improvements as well as by using automatic speech recognition. Experiments on the PASCAL CHiME challenge corpus, which contains speech corrupted by both reverberation and authentic living room noise at varying SNRs ranging from 9 to -6 dB, confirm the validity of the proposed technique. Examples of enhanced signals are available at http://www.cs.tut.fi/~tuomasv/.

Index Terms. speech enhancement, exemplar-based, noise robustness, sparse representations

Full Paper

Bibliographic reference.  Gemmeke, Jort F. / Virtanen, Tuomas / Hurmalainen, Antti (2011): "Exemplar-based speech enhancement and its application to noise-robust automatic speech recognition", In CHiME-2011, 53-57.