8th International Conference on Spoken Language Processing

Jeju Island, Korea
October 4-8, 2004

Restructuring HMM States for Speaker Adaptation in Mandarin Speech Recognition

Xianghua Xu, Qiang Guo, Jie Zhu

Shanghai Jiaotong University, China

With the tendency of posterior probability taken into account, a state-restructuring method is proposed based on confusions between HMM states. In the method, HMM state is restructured by sharing Gaussian components with its related states and the re-estimation to the increased-parameters, i.e., the inter-state weights, is derived under the EM framework. Experiments are performed on speaker-independent large vocabulary continuous Mandarin speech recognition. The results show the state-restructured systems outperform the baseline system and the combining with MLLR adaptation can lead to consistent and significant improvement on recognition accuracy over MLLR.

Full Paper

Bibliographic reference.  Xu, Xianghua / Guo, Qiang / Zhu, Jie (2004): "Restructuring HMM states for speaker adaptation in Mandarin speech recognition", In INTERSPEECH-2004, 425-428.