Title :
UBM Based Speaker Selection and Model Re-Estimation for Speaker Adaptation
Author :
Wang, Jian ; Guo, Jun ; Liu, Gang ; Lei, Jianjun
Author_Institution :
Sch. of Inf. Eng., Beijing Univ. of Posts & Telecommun.
Abstract :
Based on speaker selection, speaker adaptation technology can get a promising performance. In such system, how to represent a speaker and the computation of selection are still big issues. In this paper, we take Gaussian mixture model (GMM) as representation of a speaker, which adapted from universal background model (UBM). Likelihood ratio (LR) and cross likelihood ratio (CLR) are utilized for speaker selection. Furthermore, a single-pass re-estimation procedure, conditioned on the speaker-independent model is shown. This adaptation strategy was evaluated in a large vocabulary speech recognition task. A relative gain of 11% with respect to the baseline system is achieved
Keywords :
Gaussian processes; speaker recognition; Gaussian mixture model; cross likelihood ratio; speaker adaptation; speaker representation; speaker selection; speech recognition; universal background model; Cognitive informatics; Hidden Markov models; Loudspeakers; Maximum likelihood linear regression; Speech recognition; Statistical analysis; Statistical distributions; Telecommunication computing; Testing; Vocabulary; UBM; speaker adaptation; speaker selection;
Conference_Titel :
Cognitive Informatics, 2006. ICCI 2006. 5th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
1-4244-0475-4
DOI :
10.1109/COGINF.2006.365603
