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Transforming Features To Compensate Speech Recogniser Models For Noise

INTERSPEECH 2009: 10TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2009,..., pp.2459-2462, (2009)

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To make speech recognisers robust to noise, either the features or the models can be compensated. Feature enhancement is often fast; model compensation is often more accurate, because it predicts the corrupted speech distribution. It is therefore able, for example, to take uncertainty about the clean speech into account. This paper re-ana...More

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