A Spectrogram Model for Enhanced Source Localization and Noise-Robust ASR

This paper proposes a simple, computationally efficient 2-mixture model approach to discrimination between speech and background noise. It is directly derived from observations on real data, and can be used in a fully unsupervised manner, with the EM algorithm. A first application to sector-based, joint audio source localization and detection, using multiple microphones, confirms that the model can provide major enhancement. A second application to the single channel speech recognition task in a noisy environment yields major improvement on stationary noise and promising results on non-stationary noise.


Published in:
Proceedings of INTERSPEECH 2005
Presented at:
Proceedings of INTERSPEECH 2005
Year:
2005
Publisher:
Lisbon, Portugal
Keywords:
Note:
IDIAP-RR 05-13
Laboratories:




 Record created 2006-03-10, last modified 2018-03-17

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