Automatic generation of speech synthesis units based on closed loop training

This paper proposes a new method for automatically generating speech synthesis units. A small set of synthesis units is selected from a large speech database by the proposed Closed-Loop Training method (CLT). Because CLT is based on the evaluation and minimization of the distortion caused by the synthesis process such as prosodic modification ! the selected synthesis units are most suitable for synthesizers. In this paper, CLT is applied to a waveform concatenation based synthesizer, whose basic unit is CV/VC(diphone). It is shown that synthesis units can be efficiently generated by CLT from a labeled speech database with a small amount of computation. Moreover, the synthesized speech is clear and smooth even though the storage size of the waveform dictionary is small.