HMM-based Mandarin Singing Voice Synthesis Using Tailored Synthesis Units and Question Sets

Fluency and continuity properties are essential in synthesizing a high quality singing voice. In order to synthesize a smooth and continuous singing voice, the Hidden Markov Model-based synthesis approach is employed in this study to construct a Mandarin singing voice synthesis system. The system is designed to generate Mandarin songs with arbitrary lyrics and melody in a certain pitch range. In this study, a singing voice database is designed and collected, considering the phonetic converge of Mandarin singing voices. Synthesis units and a question set are defined carefully and tailored the meet the minimum requirement for Mandarin singing voice synthesis. In addition, pitch-shift pseudo data extension and vibrato creation are applied to obtain more natural synthesized singing voices. The evaluation results show that the system, based on tailored synthesis units and the question set, can improve the quality and intelligibility of the synthesized singing voice. Using pitch-shift pseudo data and vibrato creation can further improve the quality and naturalness of the synthesized singing voices.