7 citations · 8 across the 6 of their papers we have counts for
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cs.SD2022★ 1 cited
Noise-robust voice conversion with domain adversarial training
Hongqiang Du, Lei Xie, Haizhou Li
Voice conversion has made great progress in the past few years under the studio-quality test scenario in terms of speech quality and speaker similarity. However, in real applicatio…
eess.AS2022★ 7 cited
IQDUBBING: Prosody modeling based on discrete self-supervised speech representation for expressive voice conversion
Wendong Gan, Bolong Wen, Ying Yan +6
Prosody modeling is important, but still challenging in expressive voice conversion. As prosody is difficult to model, and other factors, e.g., speaker, environment and content, wh…