Zhaobing Han

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Robust estimate of a large number of parameters against the availability of training data is a crucial issue in triphone based continuous speech recognition. To cope with the issue, two major context-clustering methods, agglomerative (AGG) and tree-based (TB), have been widely studied. In this paper, we analyze two algorithms with respect to their(More)
Adapting the parameters of a statistical speaker independent continuous speech recognizer to the speaker can significantly improve the recognition performance and robustness of the system. In this paper, we propose a novel target-driven speaker adaptation method, Generalized Joint Maximum a Posteriori (GJMAP), which extends and improves the previous(More)
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