Remap, Warp and Attend: Non-Parallel Many-to-Many Accent Conversion with Normalizing Flows-Reference-Cited by-同舟云学术

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Remap, Warp and Attend: Non-Parallel Many-to-Many Accent Conversion with Normalizing Flows

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

Ezzerg Abdelhamid¹,Merritt Thomas¹,Yanagisawa Kayoko¹,Bilinski Piotr¹,Proszewska Magdalena¹,Pokora Kamil¹,Korzeniowski Renard¹,Barra-Chicote Roberto¹,Korzekwa Daniel¹

Affiliation:

1. Amazon Alexa

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10022052/10022330/10022506.pdf?arnumber=10022506

Reference30 articles.

1. Articulatory-based conversion of foreign accents with deep neural networks;aryal;InterSpeech,2015

2. Improving accent conversion with reference encoder and end-to-end text-to-speech;li;ArXiv,2020

3. Converting Foreign Accent Speech Without a Reference

4. Accent conversion through cross-speaker articulatory synthesis

5. Universal Neural Vocoding with Parallel Wavenet

Cited by 3 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. Controllable Accented Text-to-Speech Synthesis With Fine and Coarse-Grained Intensity Rendering;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2024

2. Comparing normalizing flows and diffusion models for prosody and acoustic modelling in text-to-speech;INTERSPEECH 2023;2023-08-20

3. Modelling Low-Resource Accents Without Accent-Specific TTS Frontend;ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2023-06-04

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