Update paper name

Author: r9y9

README.md

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 PyTorch implementation of convolutional networks-based text-to-speech synthesis models:
 
-1. [arXiv:1710.07654](https://arxiv.org/abs/1710.07654): Deep Voice 3: 2000-Speaker Neural Text-to-Speech.
+1. [arXiv:1710.07654](https://arxiv.org/abs/1710.07654): Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning.
 2. [arXiv:1710.08969](https://arxiv.org/abs/1710.08969): Efficiently Trainable Text-to-Speech System Based on Deep Convolutional Networks with Guided Attention.
 
 Audio samples are available at https://r9y9.github.io/deepvoice3_pytorch/.

docs/content/index.md

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 ## References
 
-- [Wei Ping, Kainan Peng, Andrew Gibiansky, et al, "Deep Voice 3: 2000-Speaker Neural Text-to-Speech", arXiv:1710.07654, Oct. 2017.](https://arxiv.org/abs/1710.07654)
+- [Wei Ping, Kainan Peng, Andrew Gibiansky, et al, "Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning", arXiv:1710.07654, Oct. 2017.](https://arxiv.org/abs/1710.07654)
 - [Hideyuki Tachibana, Katsuya Uenoyama, Shunsuke Aihara, "Efficiently Trainable Text-to-Speech System Based on Deep Convolutional Networks with Guided Attention". arXiv:1710.08969, Oct 2017.](https://arxiv.org/abs/1710.08969)