Feature extraction for automatic speech recognition

Abstract

An automatic speech recognition apparatus and method with a front end feature extractor that improves recognition performance under adverse acoustic conditions are disclosed. The inventive feature extractor is characterized by a critical bandwidth spectral resolution, an emphasis on slow changes in the spectral structure of the speech signal, and adaptive automatic gain control. In one the feature extractor includes a feature generator configured to compute short-term parameters of the speech signal, a filter system configured to filter the time sequences of the short-term parameters, and a normalizer configured to normalize the filtered parameters with respect to one or more previous values of the filtered parameters. Accordingly, the feature extractor is operable to carry out the following steps: computing short-term parameters of the speech signal; filtering time sequences of the short-term parameters; and normalizing the filtered parameters with respect to one or more previous values of the filtered parameters. The steps of filtering and normalizing preferably are performed independently of one another.

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