| 摘要 |
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<custom-character file="US20020042712A1-20020411-P00900.TIF" wi="20" he="20" id="custom-character-00001"/>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 voice recognition.
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