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Paper Abstract and Keywords
Presentation 2025-06-13 13:20
A Study on Improving Diffusion-Based Voice Conversion with Consistency Trajectory Models
Ryuichi Hatakeyama, Toru Nakashika (UEC) SP2025-10
Abstract (in Japanese) (See Japanese page) 
(in English) This paper proposes a fast voice-conversion framework that replaces the diffusion decoder of DDPMVC with a Consistency Trajectory Model (CTM), a model capable of learning score estimation and trajectory-consistent jumps simultaneously.
DDPMVC achieves high conversion accuracy by coupling (i) a diffusion encoder that suppresses speaker-dependent information in the input speech and (ii) a decoder that generates the target speaker’s mel-spectrogram through many steps of reverse diffusion sampling; however, its inference time is lengthy because of those sequential steps. Although diffusion-based VC already outperforms conventional deep-learning approaches in quality, its sequential sampling still limits generation speed.
CTM can predict the end point of the diffusion trajectory directly in only a few steps while yielding higher perceptual quality than the original diffusion sampler. Motivated by this property, we investigate a voice-conversion system in which the conventional diffusion decoder is entirely replaced by CTM, enabling the generation of high-quality mel-spectrograms with dramatically fewer sampling steps.
Keyword (in Japanese) (See Japanese page) 
(in English) Diffusion Model / DDPM / Consistency Trajectory Models / Voice Conversion / DDPMVC / VoiceGrad / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 74, SP2025-10, pp. 52-56, June 2025.
Paper # SP2025-10 
Date of Issue 2025-06-06 (SP) 
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)
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Conference Information
Committee SP IPSJ-SLP IPSJ-MUS  
Conference Date 2025-06-13 - 2025-06-14 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
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Paper Information
Registration To SP 
Conference Code 2025-06-SP-SLP-MUS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on Improving Diffusion-Based Voice Conversion with Consistency Trajectory Models 
Sub Title (in English)  
Keyword(1) Diffusion Model  
Keyword(2) DDPM  
Keyword(3) Consistency Trajectory Models  
Keyword(4) Voice Conversion  
Keyword(5) DDPMVC  
Keyword(6) VoiceGrad  
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Keyword(8)  
1st Author's Name Ryuichi Hatakeyama  
1st Author's Affiliation The University of Electro-Communications (UEC)
2nd Author's Name Toru Nakashika  
2nd Author's Affiliation The University of Electro-Communications (UEC)
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Speaker Author-1 
Date Time 2025-06-13 13:20:00 
Presentation Time 140 minutes 
Registration for SP 
Paper # SP2025-10 
Volume (vol) vol.125 
Number (no) no.74 
Page pp.52-56 
#Pages 5 
Date of Issue 2025-06-06 (SP) 

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