1. Arik, S., Chrzanowski, M., Coates, A., Diamos, G., Gibiansky, A., Kang,
Y., Li, X., Miller, J., Ng, A., Raiman, J., Sengupta, S., & Shoeybi, M.
(2017a). Deep Voice: Real-time neural text-to-speech. Proceedings of the
34th International Conference on Machine Learning (pp. 195-204). Sydney, AU.
6-11 August, 2017
2. Arik, S., Diamos, G., Gibiansky, A., Miller, J., Peng, K., Ping, W.,
Raiman, J., & Zhou, Y. (2017b). Deep Voice 2: Multi-speaker neural
text-to-speech. Advances in Neural Information Processing Systems 30 (pp.
2966-2974). Long Beach, CA. 4-9 December, 2017
3. Bahdanau, D., Cho, K., & Bengio, Y. (2014). Neural machine
translation by jointly learning to align and translate. Retrieved from
http://arxiv.org/abs/1409.0473 [Computing Research Repository] on January 9,
2018
4. Bengio, Y., Louradour, J., Collobert, R., & Weston, J. (2009).
Curriculum learning. Proceedings of the 26th Annual International Conference
on Machine Learning (pp. 41-48). 14-18 June, 2009
10.1145/1553374.1553380
5. Cho, K., Van Mrriёnboer, B., Gulcehre, C., Bahdanau, D., Bougares, F.,
Schwenk, H., & Bengio, Y. (2014). Learning phrase representations using
RNN encoder-decoder for statistical machine translation. Retrieved from
http://arxiv.org/abs/1406.1078 [Computing Research Repository] on January 9,
2018