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Non-parallel voice conversion (VC) is a technique for learning mappings between source and target speeches without using a parallel corpus.
Y. Stylianou, O. Cappé, and E. Moulines, “Continuous probabilistic transform for voice conversion,”
1998
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A. B. Kain, J.-P. Hosom, X. Niu, J. P. H. van Santen, M. Fried-Oken, and J. Staehely, “Improving the intelligibility of dysarthric speech,”
2007
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T. Toda, A. W. Black, and K. Tokuda, “Voice conversion based on maximum-likelihood estimation of spectral parameter trajectory,”
2007
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Z. Inanoglu and S. Young, “Data-driven emotion conversion in spoken English,”
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2010
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2012
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T. Toda, M. Nakagiri, and K. Shikano, “Statistical voice conversion techniques for body-conducted unvoiced speech enhancement,”
2012
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I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio, “Generative adversarial nets,” in
2014
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L. Sun, S. Kang, K. Li, and H. Meng, “Voice conversion using deep bidirectional long short-term memory based recurrent neural networks,” in
2015
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S. Ioffe and C. Szegedy, “Batch normalization: Accelerating deep network training by reducing internal covariate shift,” in
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L. Sun, K. Li, H. Wang, S. Kang, and H. Meng, “Phonetic posteriorgrams for many-to-one voice conversion without parallel data training,” in
2016
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F.-L. Xie, F. K. Soong, and H. Li, “A KL divergence and DNN-based approach to voice conversion without parallel training sentences,” in
2016
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C.-C. Hsu, H.-T. Hwang, Y.-C. Wu, Y. Tsao, and H.-M. Wang, “Voice conversion from non-parallel corpora using variational auto-encoder,” in
2016
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T. Zhou, P. Krähenbühl, M. Aubry, Q. Huang, and A. A. Efros, “Learning dense correspondence via 3D-guided cycle consistency,” in
2016
Cited alongside, same era.
K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in
2016
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C. Li and M. Wand, “Precomputed real-time texture synthesis with Markovian generative adversarial networks,” in
2016
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2016
Cited alongside, same era.
M. Morise, F. Yokomori, and K. Ozawa, “WORLD: A vocoder-based high-quality speech synthesis system for real-time applications,”
2016
Cited alongside, same era.
——, “CycleGAN-VC: Non-parallel voice conversion using cycle-consistent adversarial networks,” in
2018
Later among the works it cites.
H. Kameoka, T. Kaneko, K. Tanaka, and N. Hojo, “StarGAN-VC: Non-parallel many-to-many voice conversion using star generative adversarial networks,” in
2018
Later among the works it cites.
J. Lorenzo-Trueba, J. Yamagishi, T. Toda, D. Saito, F. Villavicencio, T. Kinnunen, and Z. Ling, “The voice conversion challenge 2018: Promoting development of parallel and nonparallel methods,” in
2018
Later among the works it cites.
K. Tanaka, H. Kameoka, T. Kaneko, and N. Hojo, “AttS2S-VC: Sequence-to-sequence voice conversion with attention and context preservation mechanisms,” in
2019
Later among the works it cites.
H. Kameoka, T. Kaneko, K. Tanaka, and N. Hojo, “ACVAE-VC: Non-parallel voice conversion with auxiliary classifier variational autoencoder,”
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T. Kaneko, H. Kameoka, K. Hiramatsu, and K. Kashino, “Sequence-to-sequence voice conversion with similarity metric learned using generative adversarial networks,” in
2017
Cited alongside, same era.
——, “Voice conversion from unaligned corpora using variational autoencoding Wasserstein generative adversarial networks,” in
2017
Cited alongside, same era.
2017
Cited alongside, same era.
J.-Y. Zhu, T. Park, P. Isola, and A. A. Efros, “Unpaired image-to-image translation using cycle-consistent adversarial networks,” in
2017
Cited alongside, same era.
Y. Taigman, A. Polyak, and L. Wolf, “Unsupervised cross-domain image generation,” in
2017
Cited alongside, same era.
Y. N. Dauphin, A. Fan, M. Auli, and D. Grangier, “Language modeling with gated convolutional networks,” in
2017
Cited alongside, same era.
T. Kaneko, H. Kameoka, N. Hojo, Y. Ijima, K. Hiramatsu, and K. Kashino, “Generative adversarial network-based postfilter for statistical parametric speech synthesis,” in
2017
Cited alongside, same era.
2019
Later among the works it cites.
T. Kaneko, H. Kameoka, K. Tanaka, and N. Hojo, “CycleGAN-VC2: Improved CycleGAN-based non-parallel voice conversion,” in
2019
Later among the works it cites.
T. Kaneko, H. Kameoka, K. Tanaka, and N. Hojo, “StarGAN-VC2: Rethinking conditional methods for StarGAN-based voice conversion,” in
2019
Later among the works it cites.
K. Qian, Y. Zhang, S. Chang, X. Yang, and M. Hasegawa-Johnson, “Auto-VC: Zero-shot voice style transfer with only autoencoder loss,” in
2019
Later among the works it cites.
T. Park, M.-Y. Liu, T.-C. Wang, and J.-Y. Zhu, “Semantic image synthesis with spatially-adaptive normalization,” in
2019
Later among the works it cites.
K. Kumar, R. Kumar, T. de Boissiere, L. Gestin, W. Z. Teoh, J. Sotelo, A. de Brébisson, Y. Bengio, and A. Courville, “MelGAN: Generative adversarial networks for conditional waveform synthesis,” in
2019
Later among the works it cites.
H. Kameoka, K. Tanaka, T. Kaneko, and N. Hojo, “ConvS2S-VC: Fully convolutional sequence-to-sequence voice conversion,”
2020
Closest in time.
J. Zhang, Z. Ling, and L.-R. Dai, “Non-parallel sequence-to-sequence voice conversion with disentangled linguistic and speaker representations,”
2020
Closest in time.
2020
Closest in time.
S. Lee, B. Ko, K. Lee, I.-C. Yoo, and D. Yook, “Many-to-many voice conversion using conditional cycle-consistent adversarial networks,” in
2020
Closest in time.