An Unsupervised Method to Select a Speaker Subset from Large Multi-Speaker Speech Synthesis Datasets-Reference-Cited by-同舟云学术

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An Unsupervised Method to Select a Speaker Subset from Large Multi-Speaker Speech Synthesis Datasets

Published:2020-10-25 Issue: Volume: Page:
ISSN:
Container-title:Interspeech 2020
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Author:

Gallegos Pilar Oplustil,Williams Jennifer,Rownicka Joanna,King Simon

Publisher

ISCA

Cited by 4 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. Diversity-Based Core-Set Selection for Text-to-Speech with Linguistic and Acoustic Features;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

2. Anonymizing Speaker Voices: Easy to Imitate, Difficult to Recognize?;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

3. Designing a large recording script for open-domain English speech synthesis*;Phonetics and Speech Sciences;2021-09

4. An objective evaluation of the effects of recording conditions and speaker characteristics in multi-speaker deep neural speech synthesis;Procedia Computer Science;2021

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