公开(公告)号：DE69916255D1

公开(公告)日：2004-05-13

申请号：DE69916255

申请日：1999-02-03

Applicant: QUALCOMM INC

Inventor： SIH C ,  BI NING C O QUALCOMM INCORPORA

IPC: G10L21/0208 ,  G10L15/02 ,  G10L15/06 ,  G10L15/10 ,  G10L15/20 ,  G10L21/0216

Abstract: The speech recognition training unit is modified to store digitized speech samples into a speech database that can be accessed at recognition time. The improved recognition unit comprises a noise analysis, modeling, and synthesis unit which continually analyzes the noise characteristics present in the audio environment and produces an estimated noise signal with similar characteristics. The recognition unit then constructs a noise-compensated template database by adding the estimated noise signal to each of the speech samples in the speech database and performing parameter determination on the resulting sums. This procedure accounts for the presence of noise in the recognition phase by retraining all the templates using an estimated noise signal with similar characteristics as the actual noise signal that corrupted the word to be recognized. This method improves the likelihood of a good template match, which increases the recognition accuracy.

公开(公告)号：DE69916255T2

公开(公告)日：2005-04-14

申请号：DE69916255

申请日：1999-02-03

Applicant: QUALCOMM INC

Inventor： SIH C ,  BI NING C O QUALCOMM INCORPORA

IPC: G10L21/0208 ,  G10L15/02 ,  G10L15/06 ,  G10L15/10 ,  G10L15/20 ,  G10L21/0216

Abstract: The speech recognition training unit is modified to store digitized speech samples into a speech database that can be accessed at recognition time. The improved recognition unit comprises a noise analysis, modeling, and synthesis unit which continually analyzes the noise characteristics present in the audio environment and produces an estimated noise signal with similar characteristics. The recognition unit then constructs a noise-compensated template database by adding the estimated noise signal to each of the speech samples in the speech database and performing parameter determination on the resulting sums. This procedure accounts for the presence of noise in the recognition phase by retraining all the templates using an estimated noise signal with similar characteristics as the actual noise signal that corrupted the word to be recognized. This method improves the likelihood of a good template match, which increases the recognition accuracy.