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One-shot voice conversion (VC), which performs conversion across arbitrary speakers with only a single target-speaker utterance for reference, can be effectively achieved by speech representation disentanglement.
D. Rentzos, S. Vaseghi, E. Turajlic, Q. Yan, and C.-H. Ho, “Transformation of speaker characteristics for voice conversion,” in
2003
Earlier work this paper cites.
T. Toda, A. W. Black, and K. Tokuda, “Voice conversion based on maximum-likelihood estimation of spectral parameter trajectory,”
2007
Earlier work this paper cites.
B. Gierlichs, L. Batina, P. Tuyls, and B. Preneel, “Mutual information analysis,” in
2008
Earlier work this paper cites.
D. Erro, A. Moreno, and A. Bonafonte, “Inca algorithm for training voice conversion systems from nonparallel corpora,”
2009
Earlier work this paper cites.
J. Benesty, J. Chen, Y. Huang, and I. Cohen, “Pearson correlation coefficient,” in
2009
Earlier work this paper cites.
E. Helander, T. Virtanen, J. Nurminen, and M. Gabbouj, “Voice conversion using partial least squares regression,”
2010
Earlier work this paper cites.
X. Nguyen, M. J. Wainwright, and M. I. Jordan, “Estimating divergence functionals and the likelihood ratio by convex risk minimization,”
2010
Earlier work this paper cites.
M. Gutmann and A. Hyvärinen, “Noise-contrastive estimation: A new estimation principle for unnormalized statistical models,” in
2010
Earlier work this paper cites.
D. P. Kingma and J. Ba, “Adam: A method for stochastic optimization,”
2014
Earlier work this paper cites.
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
Earlier work this paper cites.
C. Veaux, J. Yamagishi, K. MacDonald
2016
Earlier work this paper cites.
S. H. Mohammadi and A. Kain, “An overview of voice conversion systems,”
2017
Earlier work this paper cites.
K. Oyamada, H. Kameoka, T. Kaneko, H. Ando, K. Hiramatsu, and K. Kashino, “Non-native speech conversion with consistency-aware recursive network and generative adversarial network,” in
2017
Cited alongside, same era.
2017
Cited alongside, same era.
2017
Cited alongside, same era.
S. Liu, J. Zhong, L. Sun, X. Wu, X. Liu, and H. Meng, “Voice conversion across arbitrary speakers based on a single target-speaker utterance.” in
2018
Cited alongside, same era.
M. Ravanelli and Y. Bengio, “Learning speaker representations with mutual information,”
2019
Later among the works it cites.
J. Li, V. Lavrukhin, B. Ginsburg, R. Leary, O. Kuchaiev, J. M. Cohen, H. Nguyen, and R. T. Gadde, “Jasper: An end-to-end convolutional neural acoustic model,”
2019
Later among the works it cites.
D.-Y. Wu, Y.-H. Chen, and H.-y. Lee, “Vqvc+: One-shot voice conversion by vector quantization and u-net architecture,”
2020
Later among the works it cites.
B. van Niekerk, L. Nortje, and H. Kamper, “Vector-quantized neural networks for acoustic unit discovery in the zerospeech 2020 challenge,”
2020
Later among the works it cites.
K. Qian, Z. Jin, M. Hasegawa-Johnson, and G. J. Mysore, “F0-consistent many-to-many non-parallel voice conversion via conditional autoencoder,” in
2020
Later among the works it cites.
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2018
Cited alongside, same era.
M. I. Belghazi, A. Baratin, S. Rajeshwar, S. Ozair, Y. Bengio, A. Courville, and D. Hjelm, “Mutual information neural estimation,” in
2018
Cited alongside, same era.
A. v. d. Oord, Y. Li, and O. Vinyals, “Representation learning with contrastive predictive coding,”
2018
Cited alongside, same era.
H. Lu, Z. Wu, D. Dai, R. Li, S. Kang, J. Jia, and H. Meng, “One-shot voice conversion with global speaker embeddings.” in
2019
Cited alongside, same era.
K. Qian, Y. Zhang, S. Chang, X. Yang, and M. Hasegawa-Johnson, “Autovc: Zero-shot voice style transfer with only autoencoder loss,” in
2019
Cited alongside, same era.
J.-c. Chou and H.-Y. Lee, “One-shot voice conversion by separating speaker and content representations with instance normalization,”
2019
Cited alongside, same era.
2019
Cited alongside, same era.
J. Chorowski, R. J. Weiss, S. Bengio, and A. van den Oord, “Unsupervised speech representation learning using wavenet autoencoders,”
2019
Cited alongside, same era.
K. Qian, Y. Zhang, S. Chang, M. Hasegawa-Johnson, and D. Cox, “Unsupervised speech decomposition via triple information bottleneck,” in
2020
Later among the works it cites.
Y. Kwon, S.-W. Chung, and H.-G. Kang, “Intra-class variation reduction of speaker representation in disentanglement framework,”
2020
Later among the works it cites.
T.-Y. Hu, A. Shrivastava, O. Tuzel, and C. Dhir, “Unsupervised style and content separation by minimizing mutual information for speech synthesis,” in
2020
Later among the works it cites.
P. Cheng, W. Hao, S. Dai, J. Liu, Z. Gan, and L. Carin, “Club: A contrastive log-ratio upper bound of mutual information,” in
2020
Later among the works it cites.
R. Yamamoto, E. Song, and J.-M. Kim, “Parallel wavegan: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogram,” in
2020
Later among the works it cites.
Y.-H. Chen, D.-Y. Wu, T.-H. Wu, and H.-y. Lee, “Again-vc: A one-shot voice conversion using activation guidance and adaptive instance normalization,” in
2021
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