Autoregressive Variational Autoencoder with a Hidden Semi-Markov Model-Based Structured Attention for Speech Synthesis-Reference-Cited by-同舟云学术

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Autoregressive Variational Autoencoder with a Hidden Semi-Markov Model-Based Structured Attention for Speech Synthesis

Published:2022-05-23 Issue: Volume: Page:
ISSN:
Container-title:ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Fujimoto Takato¹,Hashimoto Kei¹,Nankaku Yoshihiko¹,Tokuda Keiichi¹

Affiliation:

1. Nagoya Institute of Technology,Japan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9745891/9746004/09746158.pdf?arnumber=9746158

Reference35 articles.

1. WaveGrad: Estimating gradients for waveform generation;chen;ICLRE,2021

2. Attention is all you need;vaswani;NeurIPS,2017

3. Adam: A method for stochastic optimization;kingma;ICLRE,2015

4. XIMERA: A new TTS from ATR based on corpus-based technologies;kawai;Proc SSW,2004

5. Efficiently Trainable Text-to-Speech System Based on Deep Convolutional Networks with Guided Attention

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Neural HMMS Are All You Need (For High-Quality Attention-Free TTS);ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2022-05-23

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