Abstract
This paper focuses on hidden Markov model (HMM)- based speech synthesis, which has recently been demonstrated to be very effective in generating high-quality speech and started dominating speech synthesis research. The attractive point of this approach is that the synthesized speech can easily be modified by transforming HMM parameters with a small amount of speech data. Thus it is very useful for constructing speech synthesizers with various voice characteristics, speaking styles, and emotions.
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