Learning Accent Representation with Multi-Level VAE Towards Controllable Speech Synthesis-Reference-Cited by-同舟云学术

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Learning Accent Representation with Multi-Level VAE Towards Controllable Speech Synthesis

Published:2023-01-09 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Spoken Language Technology Workshop (SLT)
language:
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Author:

Melechovsky Jan¹,Mehrish Ambuj¹,Herremans Dorien¹,Sisman Berrak²

Affiliation:

1. Singapore University of Technology and Design

2. University of Texas at Dallas

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10022052/10022330/10023072.pdf?arnumber=10023072

Reference46 articles.

1. A survey on neural speech synthesis;tan;ArXiv Preprint,2021

2. Towards end-to-end prosody trans-fer for expressive speech synthesis with tacotron;skerry-ryan;International Conference on Machine Learning,2018

3. E2E-Based Multi-Task Learning Approach to Joint Speech and Accent Recognition

4. Can voice conversion be used to reduce non-native accents?;aryal;IEEE International Conference on Acoustics Speech and Signal Processing,2014

5. Deep voice: Real-time neural text-to-speech;arik;International Conference on Machine Learning,2017

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. ASR Model Adaptation for Rare Words Using Synthetic Data Generated by Multiple Text-To-Speech Systems;2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC);2023-10-31

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