Fetching the paper…
Reading the bibliography…
In this paper, we propose the FeatherWave, yet another variant of WaveRNN vocoder combining the multi-band signal processing and the linear predictive coding.
T. Q. Nguyen, “Near-perfect-reconstruction pseudo-qmf banks,”
1994
Earlier work this paper cites.
D. P. Kingma and J. Ba, “Adam: A method for stochastic optimization,”
2005
Earlier work this paper cites.
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio, “Generative adversarial nets,” in
2014
Earlier work this paper cites.
A. Van Den Oord, S. Dieleman, H. Zen, K. Simonyan, O. Vinyals, A. Graves, N. Kalchbrenner, A. W. Senior, and K. Kavukcuoglu, “Wavenet: A generative model for raw audio.” in
2016
Earlier work this paper cites.
2017
Earlier work this paper cites.
S. Narang, E. Undersander, and G. Diamos, “Block-sparse recurrent neural networks,”
2017
Earlier work this paper cites.
2018
Earlier work this paper cites.
J. Shen, R. Pang, R. J. Weiss, M. Schuster, N. Jaitly, Z. Yang, Z. Chen, Y. Zhang, Y. Wang, R. Skerrv-Ryan
2018
Earlier work this paper cites.
W. Ping, K. Peng, and J. Chen, “Clarinet: Parallel wave generation in end-to-end text-to-speech,”
2018
Cited alongside, same era.
T. Okamoto, T. Toda, Y. Shiga, and H. Kawai, “Improving fftnet vocoder with noise shaping and subband approaches,” in
2018
Cited alongside, same era.
T. Okamoto, K. Tachibana, T. Toda, Y. Shiga, and H. Kawai, “An investigation of subband wavenet vocoder covering entire audible frequency range with limited acoustic features,” in
2018
Cited alongside, same era.
2018
Cited alongside, same era.
Z. Jin, A. Finkelstein, G. J. Mysore, and J. Lu, “Fftnet: A real-time speaker-dependent neural vocoder,” in
2019
Later among the works it cites.
L. Juvela, B. Bollepalli, V. Tsiaras, and P. Alku, “Glotnet—a raw waveform model for the glottal excitation in statistical parametric speech synthesis,”
2019
Later among the works it cites.
E. Song, K. Byun, and H.-G. Kang, “Excitnet vocoder: A neural excitation model for parametric speech synthesis systems,” in
2019
Later among the works it cites.
Z. Yao, S. Cao, W. Xiao, C. Zhang, and L. Nie, “Balanced sparsity for efficient dnn inference on gpu,” in
2019
Later among the works it cites.
Q. Tian, J. Chen, and S. Liu, “The tencent speech synthesis system for blizzard challenge 2019,” in
2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2018
Cited alongside, same era.
J.-M. Valin and J. Skoglund, “Lpcnet: Improving neural speech synthesis through linear prediction,” in
2019
Cited alongside, same era.
C. Yu, H. Lu, N. Hu, M. Yu, C. Weng, K. Xu, P. Liu, D. Tuo, S. Kang, G. Lei
2019
Cited alongside, same era.
R. Prenger, R. Valle, and B. Catanzaro, “Waveglow: A flow-based generative network for speech synthesis,” in
2019
Cited alongside, same era.
Q. Tian, X. Wan, and S. Liu, “Generative adversarial network based speaker adaptation for high fidelity wavenet vocoder,” in
Cited in the paper.
R. Korostik, A. Chirkovskiy, A. Svischev, I. Kalinovskiy, and A. Talanov, “The stc text-to-speech system for blizzard challenge 2019.”
2019
Later among the works it cites.
M.-J. Hwang, E. Song, R. Yamamoto, F. Soong, and H.-G. Kang, “Improving lpcnet-based text-to-speech with linear prediction-structured mixture density network,” in
2020
Closest in time.