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Paper Abstract and Keywords
Presentation 2026-03-03 11:00
[Poster Presentation] Spoofing attacks using deepfake speech synthesized from non-consensual recordings
Sawato Furubayashi (Tokyo Metropotitan Univ.), Shinnosuke Takamichi (Keio Univ.), Sayaka Shiota (Tokyo Metropotitan Univ.) EA2025-119 SIP2025-139 SP2025-72
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, advances in deep learning have made deepfake media increasingly difficult to distinguish from genuine content. In the speech domain, remarkable progress has been achieved, including the ability to generate synthetic speech that accurately mimics specific speakers. However, the malicious use of such technologies has become a serious concern, and improving robustness against attacks using previously unseen deepfake media has emerged as an important challenge.
In this study, we propose a method for generating high-quality deepfake speech that imitates multiple real speakers by applying speech enhancement and zero-shot text-to-speech to speech obtained through non-consensual recordings containing background noise, which are generally unsuitable for training speech synthesis models. Experimental results on countermeasure systems and automatic speaker verification systems demonstrate that the speech generated by the proposed method can successfully bypass existing speech security systems with high accuracy.
Keyword (in Japanese) (See Japanese page) 
(in English) Voice Spoofing Detection / non-consensual recording / Text-to-speech / Automatic Speaker Vertification / zero-shot text-to-speech / Audio deepfake / Voice security / J-SPAW  
Reference Info. IEICE Tech. Rep., vol. 125, no. 371, SP2025-72, pp. 277-282, March 2026.
Paper # SP2025-72 
Date of Issue 2026-02-23 (EA, SIP, SP) 
ISSN Online edition: ISSN 2432-6380
Copyright
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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 EA2025-119 SIP2025-139 SP2025-72

Conference Information
Committee SP EA SIP IPSJ-SLP  
Conference Date 2026-03-02 - 2026-03-04 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SP 
Conference Code 2026-03-SP-EA-SIP-SLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Spoofing attacks using deepfake speech synthesized from non-consensual recordings 
Sub Title (in English)  
Keyword(1) Voice Spoofing Detection  
Keyword(2) non-consensual recording  
Keyword(3) Text-to-speech  
Keyword(4) Automatic Speaker Vertification  
Keyword(5) zero-shot text-to-speech  
Keyword(6) Audio deepfake  
Keyword(7) Voice security  
Keyword(8) J-SPAW  
1st Author's Name Sawato Furubayashi  
1st Author's Affiliation Tokyo Metropolitan University (Tokyo Metropotitan Univ.)
2nd Author's Name Shinnosuke Takamichi  
2nd Author's Affiliation Keio University (Keio Univ.)
3rd Author's Name Sayaka Shiota  
3rd Author's Affiliation Tokyo Metropolitan University (Tokyo Metropotitan Univ.)
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Speaker Author-1 
Date Time 2026-03-03 11:00:00 
Presentation Time 80 minutes 
Registration for SP 
Paper # EA2025-119, SIP2025-139, SP2025-72 
Volume (vol) vol.125 
Number (no) no.369(EA), no.370(SIP), no.371(SP) 
Page pp.277-282 
#Pages
Date of Issue 2026-02-23 (EA, SIP, SP) 


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