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Singing voice conversion is a task to convert a song sang by a source singer to the voice of a target singer.
“Continuous probabilistic transform for voice conversion,”
Y. Stylianou, O. Cappe, and E. Moulines, · 1998
Earlier work this paper cites.
“Framewise phoneme classification with bidirectional lstm and other neural network architectures,”
Alex Graves and Jürgen Schmidhuber, · 2005
Earlier work this paper cites.
“Voice conversion based on maximum-likelihood estimation of spectral parameter trajectory,”
T. Toda, A. W. Black, , and K. Tokuda, · 2007
Earlier work this paper cites.
“Phoneme recognition in popular music,”
Matthias Gruhne, Konstantin Schmidt, and Christian Dittmar, · 2007
Earlier work this paper cites.
“Adaptation of a speech recognizer for singing voice,”
Annamaria Mesaros and Tuomas Virtanen, · 2009
Earlier work this paper cites.
“Applying Voice Conversion To Concatenative Singing-Voice Synthesis,”
Fernando Villavicencio and Jordi Bonada, · 2010
Earlier work this paper cites.
““INCA algorithm for training voice conversion systems from nonparallel corpora,”
D. Erro, A. Moreno, and A. Bonafonte, · 2010
Earlier work this paper cites.
“Parallel training of neural networks for speech recognition,”
K.Vesely, L. Burget, and F. Grezl, · 2010
Earlier work this paper cites.
“On the improvement of singing voice separation for monaural recordings using the mir-1k dataset,”
Chao-Ling Hsu and Jyh-Shing Roger Jang, · 2010
Cited alongside, same era.
Singing Voice Recognition for Music Information Retrieval
A Mesaros, · 2012
Cited alongside, same era.
“Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups,”
Geoffrey Hinton, Li Deng, Dong Yu, George E Dahl, Abdel-rahman Mohamed, Navdeep Jaitly, Andrew Senior, Vincent Vanhoucke, Patrick Nguyen, Tara N Sainath, et al., · 2012
Cited alongside, same era.
“Exemplar-based voice conversion using non-negative spectrogram deconvolution,”
Z. Wu, T. Virtanen, T. Kinnunen, E. S. Chng, and H. Li, · 2013
Cited alongside, same era.
“Voice conversion in high-order eigen space using Deep Belief Nets,”
T. Nakashika, R. Takashima, T. Takiguchi, and Y. Ariki, · 2013
Cited alongside, same era.
“Articulatory-based conversion of foreign accents with deep neural networks,”
Sandesh Aryal and Ricardo Gutierrez-Osuna, · 2015
Later among the works it cites.
“Video-audio driven real-time facial animation,”
Yilong Liu, Feng Xu, Jinxiang Chai, Xin Tong, Lijuan Wang, and Qiang Huo, · 2015
Later among the works it cites.
““Introducing CURRENNT: the Munich open-source CUDA RecurREnt Neural Network Toolkit,”
F. Weninger, J. Bergmann, and B. Schuller, · 2015
Later among the works it cites.
“wavenet: A generative model for raw audio,”
A van den Oord, S Dieleman, H Zen, K Simonyan, O Vinyals, A Graves, N Kalchbrenner, A Senior, and K Kavukcuoglu, · 2015
Later among the works it cites.
“Phonetic posteriorgrams for many-to-one voice conversion without parallel data training,”
Lifa Sun, Kun Li, Hao Wang, Shiyin Kang, and Helen Meng, · 2016
Later among the works it cites.
“Phonetic posteriorgrams for many-to-one voice conversion without parallel data training,”
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Alex Graves, Navdeep Jaitly, and Abdel Rahman Mohamed, · 2013
Cited alongside, same era.
“Statistical Singing Voice Conversion with direct Waveform modification based on the Spectrum Differential,”
Kazuhiro Kobayashi, Tomoki Toda, Graham Neubig, Sakriani Sakti, and Satoshi Nakamura, · 2014
Cited alongside, same era.
“Statistical singing voice conversion based on direct waveform modification with global variance,”
Kazuhiro Kobayashi, Tomoki Toda, Graham Neubig, Sakriani Sakti, and Satoshi Nakamura, · 2015
Cited alongside, same era.
S. Hochreiter and J. Schmidhuber, · 2016
Later among the works it cites.
“World: a vocoder-based high-quality speech synthesis system for real-time applications,”
Masanori Morise, Fumiya Yokomori, and Kenji Ozawa, · 2016
Later among the works it cites.