8th International Conference on Spoken Language Processing

Jeju Island, Korea
October 4-8, 2004

Evaluation of Tree-Structured Piecewise Linear Transformation-Based Noise Adaptation on AURORA2 Database

Zhipeng Zhang (1), Tomoyuki Ohya (1), Sadaoki Furui (2)

(1) NTT DoCoMo, Japan
(2) Tokyo Institute of Technology, Japan

This paper uses the AURORA2 task to investigate the performance of our proposed tree-structured piecewise linear transformation (PLT) noise adaptation. In our proposed method, an HMM that best matches the input speech is selected based on the likelihood maximization criterion by tracing a tree structured HMM space that is prepared in the training step, and the selected HMM is further adapted by linear transformation. Experimental results show that our method achieves a significant improvement for the AURORA2 database.

Full Paper

Bibliographic reference.  Zhang, Zhipeng / Ohya, Tomoyuki / Furui, Sadaoki (2004): "Evaluation of tree-structured piecewise linear transformation-based noise adaptation on AURORA2 database", In INTERSPEECH-2004, 113-116.