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What is Silent Speech to Voice Conversion Techniques about?

This paper discusses a novel approach to converting silent speech into audible voice using HMM-based statistical speech recognition and synthesis techniques. By incorporating visual information from facial movements, the system improves recognition rates and phonetic consistency of the output speech. The results indicate a 6.2% increase in recognition accuracy and a 2.7% reduction in spectral distortion, although the HMM-based system still lags behind GMM-based methods in performance.

Author

muziku.ai

Language

EN