HMM based recognition of Chinese tones in continuous speech

A novel method for recognizing Chinese tones in continuous speech is proposed in this paper. The first and second order differentials of the fundamental frequency logarithmically converted are used as feature parameters. A left-to-right Hidden Markov Modeling with five states, each of which is modeled by a single Gaussian, expresses each of Chinese tones. Non-voiced portions are coded by random values normally distributed to uniformly deal with all the time frames in an utterance. Speaker dependent tone recognition was conducted for ten speakers. The average rate of 81.8% was obtained for these speakers.