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The lack of publicly available high-quality and accurately labeled datasets has long been a major bottleneck for singing voice synthesis (SVS). To tackle this problem, we present M4Singer, a free-to-use Multi-style, Multi-singer Mandarin singing collection with elaborately annotated Musical scores as well as its benchmarks. Specifically, 1) we construct and release a large high-quality Chinese singing voice corpus, which is recorded by 20 professional singers, covering 700 Chinese pop songs as well as all the four SATB types (i.e., soprano, alto, tenor, and bass); 2) we take extensive efforts to manually compose the musical scores for each recorded song, which are necessary to the study of the prosody modeling for SVS. 3) To facilitate the use and demonstrate the quality of M4Singer, we conduct four different benchmark experiments: score-based SVS, controllable singing voice (CSV), singing voice conversion (SVC) and automatic music transcription (AMT).
Author Information
Lichao Zhang (Zhejiang University)
Ruiqi Li (Zhejiang University)
Shoutong Wang (Zhejiang University)
Liqun Deng (University of Science and Technology of China)
Jinglin Liu (Zhejiang University)
Yi Ren (Sea AI Lab)
Jinzheng He (Zhejiang University)
Rongjie Huang (Zhejiang University)
Jieming Zhu (Huawei Technologies Ltd.)
Xiao Chen (Huawei Noah's Ark Lab)
Zhou Zhao (Zhejiang University)
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2022 Spotlight: M4Singer: A Multi-Style, Multi-Singer and Musical Score Provided Mandarin Singing Corpus »
Wed. Dec 7th 01:00 -- 03:00 AM Room
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