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In this paper, the frequency characteristics of Chinese whispered speech were investigated by a filter bank analysis. It was shown that the first and the third formants were more important than the other formants in the speaker identification of Chinese whispered speech. The experiment showed that the 800-1200 Hz and 2800-3200 Hz ranges were the most significant frequency ranges in discriminating the speaker. Based on this result, a new feature scale named whisper sensitive scale (WSS) was proposed to replace the common scale, Mel scale, and to extract the cepstral coefficient from whispered speech signal. Furthermore, a speaker identification system in whispered speech was presented based on the modified Hidden Markov Models integrating advantages of WSCC (the whisper sensitive cepstral coefficient) and LPCC. And the new system performed better in solving the problem of speaker identification of Chinese whispered speech than the traditional method.
In this paper, the frequency characteristics of Chinese whispered speech were investigated by a filter bank analysis. It was shown that the first and the third formants were more important than the other formants in the speaker identification of Chinese whispered speech. Based on this result, a new feature scale named whisper sensitive scale (WSS) was proposed to replace the common scale, Mel scale, and to extract the cepstral coefficient from whispered speech signal. And, a speaker identification system in whispered speech was presented based on the modified Hidden Markov Models integrating advantages of WSCC (the whisper sensitive cepstral coefficient) and LPCC. And the new system performed better in solving the problem of speaker identification of Chinese whispered speech than the traditional method.