Speech recognition system with an adaptive acoustic model

Abstract

At the time of the speaker adaptation, first feature vector generation sections () generate a feature vector series [C] from which the additive noise and multiplicative noise are removed. A second feature vector generation section () generates a feature vector series [S] including the features of the additive noise and multiplicative noise. A path search section () conducts a path search by comparing the feature vector series [C] to the standard vector [a] of the standard voice HMM (). When the speaker adaptation section () conducts correlation operation on an average feature vector [S^] of the standard vector [a] corresponding to the path search result Dv and the feature vector series [S], the adaptive vector [x] is generated. The adaptive vector [x] updates the feature vector of the speaker adaptive acoustic model () used for the speech recognition.