The paper reports recent efforts to further improve the performance of the Sphinx system for speaker-independent continuous speech recognition. The recognition error rate is significantly reduced with incorporation of additional dynamic features, semi-continuous hidden Markov models, and speaker clustering. For the June 1990 (RM2) evaluation test set, the error rates of our current system are 4.3% and 19.9% for word-pair grammar and no grammar respectively.
Improved hidden Markov modeling for speaker-independent continuous speech recognition
- Xuedong Huang ,
- Fil Alleva ,
- Satoru Hayamizu ,
- Hsiao-Wuen Hon ,
- Mei-Yuh Hwang ,
- Kai-Fu Lee
HLT '90 Proceedings of the workshop on Speech and Natural Language |