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We present Deep Voice 3, a fully-convolutional attention-based neural text-to-speech (TTS) system.
Signal estimation from modified short-time fourier transform
Daniel Griffin and Jae Lim · 1984
Earlier work this paper cites.
Restructuring speech representations using a pitch-adaptive time–frequency smoothing and an instantaneous-frequency-based f0 extraction: Possible role of a repetitive structure in sounds
Hideki Kawahara, Ikuyo Masuda-Katsuse, and Alain De Cheveigne · 1999
Earlier work this paper cites.
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Paul Taylor · 2009
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Junichi Yamagishi, Takashi Nose, Heiga Zen, Zhen-Hua Ling, Tomoki Toda, Keiichi Tokuda, Simon King, and Steve Renals · 2009
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Junichi Yamagishi, Bela Usabaev, Simon King, Oliver Watts, John Dines, Jilei Tian, Yong Guan, Rile Hu, Keiichiro Oura, Yi-Jian Wu, et al · 2010
Earlier work this paper cites.
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Earlier work this paper cites.
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Kyunghyun Cho, Bart Van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio · 2014
Earlier work this paper cites.
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Ilya Sutskever, Oriol Vinyals, and Quoc V Le · 2014
Earlier work this paper cites.
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Yannis Agiomyrgiannakis · 2015
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio · 2015
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Attention-based models for speech recognition
Jan K Chorowski, Dzmitry Bahdanau, Dmitriy Serdyuk, Kyunghyun Cho, and Yoshua Bengio · 2015
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Librispeech: an ASR corpus based on public domain audio books
Vassil Panayotov, Guoguo Chen, Daniel Povey, and Sanjeev Khudanpur · 2015
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A neural attention model for abstractive sentence summarization
Alexander M Rush, Sumit Chopra, and Jason Weston · 2015
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Recent advances in Google real-time HMM-driven unit selection synthesizer
Xavi Gonzalvo, Siamak Tazari, Chun-an Chan, Markus Becker, Alexander Gutkin, and Hanna Silen · 2016
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WORLD: A vocoder-based high-quality speech synthesis system for real-time applications
Masanori Morise, Fumiya Yokomori, and Kenji Ozawa · 2016
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Siri on-device deep learning-guided unit selection text-to-speech system
Tim Capes, Paul Coles, Alistair Conkie, Ladan Golipour, Abie Hadjitarkhani, Qiong Hu, Nancy Huddleston, Melvyn Hunt, Jiangchuan Li, Matthias Neeracher, et al · 2017
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Yann Dauphin, Angela Fan, Michael Auli, and David Grangier · 2017
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Soroush Mehri, Kundan Kumar, Ishaan Gulrajani, Rithesh Kumar, Shubham Jain, Jose Sotelo, Aaron Courville, and Yoshua Bengio · 2017
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Colin Raffel, Thang Luong, Peter J Liu, Ron J Weiss, and Douglas Eck · 2017
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Char2wav: End-to-end speech synthesis
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Deep Voice: Real-time neural text-to-speech
Sercan Ö. Arık, Mike Chrzanowski, Adam Coates, Gregory Diamos, Andrew Gibiansky, Yongguo Kang, Xian Li, John Miller, Jonathan Raiman, Shubho Sengupta, and Mohammad Shoeybi · 2017
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Deep Voice 2: Multi-speaker neural text-to-speech
Sercan Ö. Arık, Gregory Diamos, Andrew Gibiansky, John Miller, Kainan Peng, Wei Ping, Jonathan Raiman, and Yanqi Zhou · 2017
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Chris Bagwell · 2017
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Jose Sotelo, Soroush Mehri, Kundan Kumar, Joao Felipe Santos, Kyle Kastner, Aaron Courville, and Yoshua Bengio · 2017
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Voice synthesis for in-the-wild speakers via a phonological loop
Yaniv Taigman, Lior Wolf, Adam Polyak, and Eliya Nachmani · 2017
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Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Yuxuan Wang, RJ Skerry-Ryan, Daisy Stanton, Yonghui Wu, Ron Weiss, Navdeep Jaitly, Zongheng Yang, Ying Xiao, Zhifeng Chen, Samy Bengio, Quoc Le, Yannis Agiomyrgiannakis, Rob Clark, and Rif A. Saurous · 2017
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