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When Counterpoint Meets Chinese Folk Melodies
Nan Jiang · Sheng Jin · Zhiyao Duan · Changshui Zhang

Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #980

Counterpoint is an important concept in Western music theory. In the past century, there have been significant interests in incorporating counterpoint into Chinese folk music composition. In this paper, we propose a reinforcement learning-based system, named FolkDuet, towards the online countermelody generation for Chinese folk melodies. With no existing data of Chinese folk duets, FolkDuet employs two reward models based on out-of-domain data, i.e. Bach chorales, and monophonic Chinese folk melodies. An interaction reward model is trained on the duets formed from outer parts of Bach chorales to model counterpoint interaction, while a style reward model is trained on monophonic melodies of Chinese folk songs to model melodic patterns. With both rewards, the generator of FolkDuet is trained to generate countermelodies while maintaining the Chinese folk style. The entire generation process is performed in an online fashion, allowing real-time interactive human-machine duet improvisation. Experiments show that the proposed algorithm achieves better subjective and objective results than the baselines.

Author Information

Nan Jiang (Tsinghua University)
Sheng Jin (Tsinghua University)
Zhiyao Duan (Unversity of Rochester)
Changshui Zhang (Tsinghua University)

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