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Generative adversarial network-based approach to signal reconstruction from magnitude spectrogram.

, , , , , and . EUSIPCO, page 2514-2518. IEEE, (2018)

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AttS2S-VC: Sequence-to-Sequence Voice Conversion with Attention and Context Preservation Mechanisms., , , and . CoRR, (2018)ConvS2S-VC: Fully convolutional sequence-to-sequence voice conversion., , , and . CoRR, (2018)iSTFTNet2: Faster and More Lightweight iSTFT-Based Neural Vocoder Using 1D-2D CNN., , , and . CoRR, (2023)FastS2S-VC: Streaming Non-Autoregressive Sequence-to-Sequence Voice Conversion., , and . CoRR, (2021)Collection and Analysis of Dialogues Provided by Two Speakers Acting as One., , , , , , and . SIGdial, page 323-328. Association for Computational Linguistics, (2020)Generative adversarial network-based approach to signal reconstruction from magnitude spectrogram., , , , , and . EUSIPCO, page 2514-2518. IEEE, (2018)The ASVspoof 2019 database., , , , , , , , , and 30 other author(s). CoRR, (2019)ATTS2S-VC: Sequence-to-sequence Voice Conversion with Attention and Context Preservation Mechanisms., , , and . ICASSP, page 6805-6809. IEEE, (2019)StarGAN-VC: non-parallel many-to-many Voice Conversion Using Star Generative Adversarial Networks., , , and . SLT, page 266-273. IEEE, (2018)Cyclegan-VC2: Improved Cyclegan-based Non-parallel Voice Conversion., , , and . ICASSP, page 6820-6824. IEEE, (2019)