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Given a piece of music, ChoreoMaster can automatically generate a high-quality dance motion sequence to accompany the input music in terms of style, rhythm and structure. To achieve this goal, we introduce a novel choreography-oriented choreomusical embedding framework, which successfully constructs a unified choreomusical embedding space for both style and rhythm relationships between music and dance phrases. The learned choreomusical embedding is then incorporated into a novel choreography-oriented graph-based motion synthesis framework, which can robustly and efficiently generate high-quality dance motions following various choreographic rules. Moreover, as a production-ready system, ChoreoMaster is sufficiently controllable and comprehensive for users to produce desired results. Experimental results demonstrate that dance motions generated by ChoreoMaster are accepted by professional artists.<\/jats:p>","DOI":"10.1145\/3450626.3459932","type":"journal-article","created":{"date-parts":[[2021,7,20]],"date-time":"2021-07-20T00:04:27Z","timestamp":1626739467000},"page":"1-13","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":76,"title":["ChoreoMaster"],"prefix":"10.1145","volume":"40","author":[{"given":"Kang","family":"Chen","sequence":"first","affiliation":[{"name":"NetEase Games AI LAB, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhipeng","family":"Tan","sequence":"additional","affiliation":[{"name":"NetEase Games AI LAB, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jin","family":"Lei","sequence":"additional","affiliation":[{"name":"NetEase Games AI LAB, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Song-Hai","family":"Zhang","sequence":"additional","affiliation":[{"name":"Tsinghua University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuan-Chen","family":"Guo","sequence":"additional","affiliation":[{"name":"Tsinghua University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weidong","family":"Zhang","sequence":"additional","affiliation":[{"name":"NetEase Games AI LAB, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shi-Min","family":"Hu","sequence":"additional","affiliation":[{"name":"Tsinghua University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2021,7,19]]},"reference":[{"key":"e_1_2_2_1_1","volume-title":"GrooveNet: Real-time music-driven dance movement generation using artificial neural networks. networks 8, 17","author":"Alemi Omid","year":"2017","unstructured":"Omid Alemi , Jules Fran\u00e7oise , and Philippe Pasquier . 2017. 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