Towards Multi-Scale Style Control for Expressive Speech Synthesis

H. Ze, A. Senior, and M. Schuster, “Statistical parametric speech synthesis using deep neural networks,” in 2013 IEEE International Conference on Acoustics, Speech and Signal Processing . IEEE, 2013, pp. 7962–7966

2013

Earlier work this paper cites.

M. Steinschneider, K. V. Nourski, and Y. I. Fishman, “Representation of speech in human auditory cortex: is it special?” Hearing research , vol. 305, pp. 57–73, 2013

2013

Earlier work this paper cites.

Y. Qian, Y. Fan, W. Hu, and F. K. Soong, “On the training aspects of deep neural network (dnn) for parametric tts synthesis,” in 2014 IEEE International Conference on Acoustics, Speech and Signal Processing . IEEE, 2014, pp. 3829–3833

2014

Earlier work this paper cites.

K. Cho, B. van Merrienboer, Ç. Gülçehre, D. Bahdanau, F. Bougares, H. Schwenk, and Y. Bengio, “Learning phrase representations using RNN encoder-decoder for statistical machine translation,” in Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing , A. Moschitti, B. Pang, and W. Daelemans, Eds. ACL, 2014, pp. 1724–1734

2014

Earlier work this paper cites.

S. Ioffe and C. Szegedy, “Batch normalization: Accelerating deep network training by reducing internal covariate shift,” in International conference on machine learning . PMLR, 2015, pp. 448–456

2015

Earlier work this paper cites.

Y. Wang, R. Skerry-Ryan, D. Stanton, Y. Wu, R. J. Weiss, N. Jaitly, Z. Yang, Y. Xiao, Z. Chen, S. Bengio, Q. Le, Y. Agiomyrgiannakis, R. Clark, and R. A. Saurous, “Tacotron: Towards end-to-end speech synthesis,” in Proc. Interspeech 2017 , 2017, pp. 4006–4010

2017

Earlier work this paper cites.

A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. u. Kaiser, and I. Polosukhin, “Attention is all you need,” in Advances in Neural Information Processing Systems , I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett, Eds., vol. 30. Curran Associates, Inc., 2017

2017

Cited alongside, same era.

J. Shen, R. Pang, R. J. Weiss, M. Schuster, N. Jaitly, Z. Yang, Z. Chen, Y. Zhang, Y. Wang, R. Skerrv-Ryan et al. , “Natural tts synthesis by conditioning wavenet on mel spectrogram predictions,” in 2018 IEEE International Conference on Acoustics, Speech and Signal Processing . IEEE, 2018, pp. 4779–4783

2018

Cited alongside, same era.

R. Skerry-Ryan, E. Battenberg, Y. Xiao, Y. Wang, D. Stanton, J. Shor, R. Weiss, R. Clark, and R. A. Saurous, “Towards end-to-end prosody transfer for expressive speech synthesis with tacotron,” in International Conference on Machine Learning . PMLR, 2018, pp. 4693–4702

2018

Cited alongside, same era.

V. Klimkov, S. Ronanki, J. Rohnke, and T. Drugman, “Fine-Grained Robust Prosody Transfer for Single-Speaker Neural Text-To-Speech,” in Proc. Interspeech 2019 , 2019, pp. 4440–4444

2019

Later among the works it cites.

X. Zhu, S. Yang, G. Yang, and L. Xie, “Controlling emotion strength with relative attribute for end-to-end speech synthesis,” in 2019 IEEE Automatic Speech Recognition and Understanding Workshop . IEEE, 2019, pp. 192–199

2019

Later among the works it cites.

T. Daxin and L. Tan, “Fine-grained style modelling and transfer in text-to-speech synthesis via content-style disentanglement,” arXiv preprint arXiv:2011.03943 , 2020

Original

2020

Later among the works it cites.

J. Kong, J. Kim, and J. Bae, “Hifi-gan: Generative adversarial networks for efficient and high fidelity speech synthesis,” in Advances in Neural Information Processing Systems , H. Larochelle, M. Ranzato, R. Hadsell, M. Balcan, and H. Lin, Eds., 2020

Original

2020

Later among the works it cites.