대한전자공학회:학술대회논문집 (Proceedings of the IEEK Conference)
- 대한전자공학회 2002년도 하계종합학술대회 논문집(4)
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- Pages.195-198
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- 2002
High-Performance 음성 인식을 위한 Efficient Mixture Gaussian 합성에 관한 연구
A Study on Gaussian Mixture Synthesis for High-Performance Speech Recognition
초록
We propose an efficient mixture Gaussian synthesis method for decision tree based state tying that produces better context-dependent models in a short period of training time. This method makes it possible to handle mixture Gaussian HMMs in decision tree based state tying algorithm, and provides higher recognition performance compared to the conventional HMM training procedure using decision tree based state tying on single Gaussian GMMs. This method also reduces the steps of HMM training procedure. We applied this method to training of PBS, and we expect to achieve a little point improvement in phoneme accuarcy and reduction in training time.
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