Mandarin Singing Voice Synthesis Based on Harmonic Plus Noise Model and Singing Expression Analysis
This work addresses the challenge of making Mandarin singing voice synthesis more human-like and expressive, though it is incremental as it builds on existing harmonic plus noise models with added expression analysis.
The study tackled the problem of synthesizing expressive Mandarin singing voices by analyzing six acoustic, phonetic, and musical factors from real singing signals and integrating them into a harmonic plus noise model-based system, resulting in notable improvements in perceptual naturalness, clearness, and expressiveness.
The purpose of this study is to investigate how humans interpret musical scores expressively, and then design machines that sing like humans. We consider six factors that have a strong influence on the expression of human singing. The factors are related to the acoustic, phonetic, and musical features of a real singing signal. Given real singing voices recorded following the MIDI scores and lyrics, our analysis module can extract the expression parameters from the real singing signals semi-automatically. The expression parameters are used to control the singing voice synthesis (SVS) system for Mandarin Chinese, which is based on the harmonic plus noise model (HNM). The results of perceptual experiments show that integrating the expression factors into the SVS system yields a notable improvement in perceptual naturalness, clearness, and expressiveness. By one-to-one mapping of the real singing signal and expression controls to the synthesizer, our SVS system can simulate the interpretation of a real singer with the timbre of a speaker.