世界音乐
人工智能大会
2021 北京

中央音乐学院/民族文化宫
2021年10月22-24日

江 超

江超,毕业于南京大学,获电子学学士学位,声学硕士学位。全国电声学标准化技术委员会委员,中国声学学会音频工程分会委员,中国电子元件行业协会技术委员。2019年成为中央音乐学院音乐人工智能与音乐信息科技专业博士研究生,师从俞峰教授和吴玺宏教授。

Research on Singing Inverse Method Based on Pronunciation Physical Model

A novel singing inverse method is presented in this report. A complete pronunciation physical model is constructed by using the Two Mass model of vocal cord vibration and the Tube Resonance Model (TRM) of vocal tract. By employing the physical model, speech and singing voice can be synthesized by vocal cord and vocal tract physical parameters. A new self-supervised approach is presented to solve inverse problem. The proposed approach works is an analysis-by-synthesis way to learn an inference network by iterative sampling and training. The result has an explicit physical meanings. By this method, we can retrieve the physical parameters of vocal cords and tract of singers through the singing signal, so as to quantitatively analyze the technical characteristics of singers of different parts and singing styles.