5th International Conference on Spoken Language Processing
In this paper, we presented an integrated on-line learning scheme, which combined the state-of-art speaker normalization and adaptation techniques to improve the performance of our large vocabulary Chinese continuous speech recognition (CSR) system. We used VTLN to remove inter-speaker variation in both training and testing stage. To facilitate dynamic transformation scale determination, we devised a tree-based transformation method as the key component of our incremental adaptation. Experiments shows that the combined scheme of on-line learning (incremental & unsupervised) system, which gives approximately 22~26% error reduction rate, was proved to be better than either method when used separately at 18.34% and 2.7%.
Bibliographic reference. Zheng, Rong / Wang, Zuoying (1998): "Toward on-line learning of Chinese continuous speech recognition system", In ICSLP-1998, paper 0276.