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Avocodo: Generative Adversarial Network for Artifact-Free Vocoder

AAAI 2023 · Image generation › GANs · approach: GAN vocoders and audio synthesis · 27 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Replace HiFi-GAN V1 with Avocodo V1GAN-based vocoder · LJSpeech testF0 RMSE: 35.96 -> 33.98Helped
Replace HiFi-GAN V1 with Avocodo V1GAN-based vocoder · LJSpeech testLSD-HF: 9.72 -> 9.13Helped
Replace HiFi-GAN V1 with Avocodo V1GAN-based vocoder · LJSpeech testPESQ: 3.64 -> 3.81Helped
Replace HiFi-GAN V1 with Avocodo V1GAN-based vocoder · Unseen(EN)MOS: 3.940(±0.09) -> 4.080(±0.08)Helped
Replace HiFi-GAN V1 with Avocodo V1GAN-based vocoder · Unseen(KR)MOS: 3.810(±0.06) -> 3.972(±0.07)Helped
Use CoMBD instead of MSD (ablation)Avocodo generator V2 · LJSpeech single-speaker comparisonMOS: 3.743 (±0.07) -> 4.156 (±0.05)Helped
Use SBD instead of MPD (ablation)Avocodo generator V2 · LJSpeech single-speaker comparisonMOS: 3.675 (±0.08) -> 4.130 (±0.06)Helped
Use PQMF downsampling instead of naive downsamplingGAN-based vocoder training · High-pitch singing voiceF0 reconstructionHelped
Add collaborative multi-scale and hierarchical discrimination of intermediate and downsampled outputsAvocodo generator · Speech waveform synthesisupsampling artifactsHelped
Discriminate PQMF-decomposed sub-band signals with SBD (ablation)Avocodo generator · LJSpeech single-speaker comparisonMOS: 3.675 (±0.08) -> 4.130 (±0.06)Helped

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