Publication | Closed Access
The Singing Voice Conversion Challenge 2023
39
Citations
37
References
2023
Year
Unknown Venue
MusicEngineeringMachine LearningVoice EvaluationSpeech RecognitionNatural Language ProcessingData ScienceRobust Speech RecognitionVoice RecognitionHealth SciencesVoice ConversionSpeech SynthesisVoice Conversion ChallengeSpeech OutputComputer ScienceSpeech CommunicationVoiceSpeech ProcessingCross-domain SvcSpeech PerceptionVoice TechnologySpeaker Recognition
We present the latest iteration of the voice conversion challenge (VCC) series, a bi-annual scientific event aiming to compare and understand different voice conversion (VC) systems based on a common dataset. This year we shifted our focus to singing voice conversion (SVC), thus named the challenge the Singing Voice Conversion Challenge (SVCC). A new database was constructed for two tasks, namely in-domain and cross-domain SVC. The challenge was run for two months, and in total we received 26 submissions, including 2 baselines. Through a large-scale crowd-sourced listening test, we observed that for both tasks, although human-level naturalness was achieved by the top system, no team was able to obtain a similarity score as high as the target speakers. Also, as expected, cross-domain SVC is harder than in-domain SVC, especially in the similarity aspect. We also investigated whether existing objective measurements were able to predict perceptual performance, and found that only few of them could reach a significant correlation.
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