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Recent trends in neural network based text-to-speech/speech synthesis pipelines have employed recurrent Seq2seq architectures that can synthesize realistic sounding speech directly from text characters.
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Paul Taylor. Text-to-Speech Synthesis. Cambridge University Press, New York, NY, USA, 1st edition, 2009. ISBN 0521899273, 9780521899277
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Chorowski, Jan K., et al. "Attention-based models for speech recognition." Advances in neural information processing systems. 2015
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Morise, Masanori, Fumiya Yokomori, and Kenji Ozawa. "WORLD: a vocoder-based high-quality speech synthesis system for real-time applications." IEICE TRANSACTIONS on Information and Systems 99.7 (2016): 1877-1884
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Van Den Oord, Aäron, et al. "WaveNet: A generative model for raw audio." SSW. 2016
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Wang, Yuxuan, et al. "Tacotron: A fully end-to-end text-to-speech synthesis model." arXiv preprint (2017)
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Vaswani, Ashish, et al. "Attention is all you need." Advances in Neural Information Processing Systems. 2017
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Shen, Jonathan, et al. "Natural tts synthesis by conditioning wavenet on mel spectrogram predictions." 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2018
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Tachibana, Hideyuki, Katsuya Uenoyama, and Shunsuke Aihara. "Efficiently trainable text-to-speech system based on deep convolutional networks with guided attention." 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2018
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