Data as of Jul 25, 2026 · Based on 2,718,867 AI responses across 9,511 prompts · See how Parse measures this
StreamVCmiracyan.github.io · Low evidenceMiracyan.github.io presents a recognition-synthesis method for non-parallel voice conversion that uses adversarial learning to achieve speaker-independent hidden representations. The approach, which outperformed the VCC2018 baseline, employs a recognizer and synthesizer trained with text classification loss and GAN-based fine-tuning to prevent over-smoothing.
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arxiv.org shapes more of what AI says about StreamVC than any other source, at 100% of its citations.