Second International Conference on Spoken Language Processing (ICSLP'92)
Banff, Alberta, Canada
In this paper, we present a speaker adaptation technique based on corrective training(CT) and learning vector quantization (LVQ). Our algorithm consists of two stages: codebook adaptation and hidden Markov model(HMM) parameter adaptation. In the stage of codebook adaptation, we propose a codebook adaptation scheme using a neurally-inspired LVQ with highly discriminant ability. In the stage of HMM parameter adaptation, we propose a modified corrective training algorithm for speaker adaptation in which the HMM parameter adaptation obtained by probability transformation matrix arc re-estimated to maximize the recognition rate on the adaptation speech. With this method, the recognition rate for new speakers can be improved.
Bibliographic reference. Koo, Myoung-Wan / Un, Chong-Kwan (1992): "A speaker adaptation based on corrective training and learning vector quantization", In ICSLP-1992, 1475-1478.