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Paper Abstract and Keywords
Presentation 2023-10-14 16:40
Sequence-to-sequence Voice Conversion for Electrolaryngeal Speech Enhancement with Multi-stage Pretraining and Fine-tuning Techniques
Ding Ma, Lester Phillip Violeta, Kazuhiro Kobayashi, Tomoki Toda (Nagoya Univ.) SP2023-32 WIT2023-23
Abstract (in Japanese) (See Japanese page) 
(in English) Sequence-to-sequence (seq2seq) voice conversion (VC) models have great potential for electrolaryngeal (EL) speech to normal speech converison (EL2SP). However, applying seq2seq VC on EL2SP faces challenges due to the need for vast and high-quality parallel training data. On the other hand, it is difficult to conduct effective transfer learning from normal speech to EL2SP dataset, owing to the substantial differences in acoustic features between EL and normal speech domains. To address above problems, we present novel methods with the multi-stage pretraining and fine-tuning techniques. We first employ encoder adaptation training for a pretrained seq2seq model with imperfect synthetic and original EL data. Then, we incorporate both imperfect synthetic and original parallel data for VC training. The final fine-tuning of EL2SP only uses the original dataset. The experimental results demonstrate that our approach yields significant improvements in EL2SP performance.
Keyword (in Japanese) (See Japanese page) 
(in English) Sequence-to-sequence / voice conversion / electrolaryngeal speech / pretraining / fine-tuning / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 212, SP2023-32, pp. 27-32, Oct. 2023.
Paper # SP2023-32 
Date of Issue 2023-10-07 (SP, WIT) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF SP2023-32 WIT2023-23

Conference Information
Committee WIT SP IPSJ-SLP  
Conference Date 2023-10-14 - 2023-10-14 
Place (in Japanese) (See Japanese page) 
Place (in English) Kyushu Institute of Technology 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Speech and Well-being Information Technology, etc. 
Paper Information
Registration To SP 
Conference Code 2023-10-WIT-SP-SLP 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Sequence-to-sequence Voice Conversion for Electrolaryngeal Speech Enhancement with Multi-stage Pretraining and Fine-tuning Techniques 
Sub Title (in English)  
Keyword(1) Sequence-to-sequence  
Keyword(2) voice conversion  
Keyword(3) electrolaryngeal speech  
Keyword(4) pretraining  
Keyword(5) fine-tuning  
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1st Author's Name Ding Ma  
1st Author's Affiliation Nagoya University (Nagoya Univ.)
2nd Author's Name Lester Phillip Violeta  
2nd Author's Affiliation Nagoya University (Nagoya Univ.)
3rd Author's Name Kazuhiro Kobayashi  
3rd Author's Affiliation Nagoya University (Nagoya Univ.)
4th Author's Name Tomoki Toda  
4th Author's Affiliation Nagoya University (Nagoya Univ.)
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Speaker Author-1 
Date Time 2023-10-14 16:40:00 
Presentation Time 25 minutes 
Registration for SP 
Paper # SP2023-32, WIT2023-23 
Volume (vol) vol.123 
Number (no) no.212(SP), no.213(WIT) 
Page pp.27-32 
#Pages 6 
Date of Issue 2023-10-07 (SP, WIT) 

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