Model-based compensation of the additive noise for continuous speech recognition. experiments using the Aurora II database and tasks

@inproceedings{Segura2001ModelbasedCO,
  title={Model-based compensation of the additive noise for continuous speech recognition. experiments using the Aurora II database and tasks},
  author={Jos{\'e} C. Segura and {\'A}ngel de la Torre and M. Carmen Ben{\'i}tez and Antonio M. Peinado},
  booktitle={INTERSPEECH},
  year={2001}
}
In this paper we apply a model-based compensation method to cancel the effect of the additive noise in Automatic Speech Recognition systems. The method is formulated in a statistical framework in order to perform the optimal compensation of the noise effect given the observed noisy speech, a model describing the statistics of the speech recorded in a clean reference environment and the estimation of the noise in the noisy recognition environment. The noise is estimated using the first frames of… CONTINUE READING
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