TechWare: HMM-based speech synthesis resources [Best of the Web]
Heiga Zen, Keiichi Tokuda · IEEE Signal Processing Magazine · 2009
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.