Speech recognition system with an adaptive acoustic model

Abstract

At the time of the speaker adaptation, first feature vector generation sections (7, 8, 9) generate a feature vector series [Ci, M] from which the additive noise and multiplicative noise are removed. A second feature vector generation section (12) generates a feature vector series [Si, M] including the features of the additive noise and multiplicative noise. A path search section (10) conducts a path search by comparing the feature vector series [Ci, m] to the standard vector [an, m] of the standard voice HMM (300). When the speaker adaptation section (11) conducts correlation operation on an average feature vector [S^n, m] of the standard vector [an, m] corresponding to the path search result Dv and the feature vector series [Si, m], the adaptive vector [xn, m] is generated. The adaptive vector [xn, m] updates the feature vector of the speaker adaptive acoustic model (400) used for the speech recognition.

Dependencies are inferred from the claim text.