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We present the latest iteration of the voice conversion challenge (VCC)series, a bi-annual scientific event aiming to compare and understand differentvoice conversion (VC) systems based on a common dataset. This year we shiftedour focus to singing voice conversion (SVC), thus named the challenge theSinging Voice Conversion Challenge (SVCC). A new database was constructed fortwo tasks, namely in-domain and cross-domain SVC. The challenge was run for twomonths, and in total we received 26 submissions, including 2 baselines. Througha large-scale crowd-sourced listening test, we observed that for both tasks,although human-level naturalness was achieved by the top system, no team wasable to obtain a similarity score as high as the target speakers. Also, asexpected, cross-domain SVC is harder than in-domain SVC, especially in thesimilarity aspect. We also investigated whether existing objective measurementswere able to predict perceptual performance, and found that only few of themcould reach a significant correlation.

The Singing Voice Conversion Challenge 2023