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Paper Abstract and Keywords
Presentation 2026-01-19 13:25
Multilingual Audio Deepfake detection: A Robust and Generalizable Hybrid Model Approach
Candy Olivia Mawalim, Yutong Wang,, Aulia Adila, Shogo Okada, Masashi Unoki (JAIST) EMM2025-102
Abstract (in Japanese) (See Japanese page) 
(in English) This paper introduces a robust approach to multilingual audio deepfake detection, addressing the critical challenge posed by increasingly sophisticated AI-generated voices within the context of the SAFE Challenge evaluation. To build a system capable of generalizing across diverse linguistic and acoustic environments, the study utilized a comprehensive evaluation corpus covering 17 languages and a broad spectrum of synthesis methods. The core contribution is a hybrid detection model that synergistically combines the established RawNet and AASIST architectures with language-agnostic representations derived from a multilingual self-supervised learning model. Furthermore, the efficacy of RawBoost data augmentation was explored to enhance robustness against real-world noise. Experimental evaluation confirms the system’s promising generalization capabilities, achieving approximately 73% balanced accuracy across the diverse multilingual data and on previously unseen synthesis algorithms.
Keyword (in Japanese) (See Japanese page) 
(in English) multilingual / deepfake / speech synthesis / hybrid model / / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 317, EMM2025-102, pp. 7-12, Jan. 2026.
Paper # EMM2025-102 
Date of Issue 2026-01-12 (EMM) 
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 EMM2025-102

Conference Information
Committee EMM  
Conference Date 2026-01-19 - 2026-01-20 
Place (in Japanese) (See Japanese page) 
Place (in English) Tohoku Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Sense of Presence, Universal Media, Digital Entertainment, etc. 
Paper Information
Registration To EMM 
Conference Code 2026-01-EMM 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Multilingual Audio Deepfake detection: A Robust and Generalizable Hybrid Model Approach 
Sub Title (in English)  
Keyword(1) multilingual  
Keyword(2) deepfake  
Keyword(3) speech synthesis  
Keyword(4) hybrid model  
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1st Author's Name Candy Olivia Mawalim  
1st Author's Affiliation Japan Advanced Institute of Science and Technology (JAIST)
2nd Author's Name Yutong Wang,  
2nd Author's Affiliation Japan Advanced Institute of Science and Technology (JAIST)
3rd Author's Name Aulia Adila  
3rd Author's Affiliation Japan Advanced Institute of Science and Technology (JAIST)
4th Author's Name Shogo Okada  
4th Author's Affiliation Japan Advanced Institute of Science and Technology (JAIST)
5th Author's Name Masashi Unoki  
5th Author's Affiliation Japan Advanced Institute of Science and Technology (JAIST)
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Speaker Author-5 
Date Time 2026-01-19 13:25:00 
Presentation Time 25 minutes 
Registration for EMM 
Paper # EMM2025-102 
Volume (vol) vol.125 
Number (no) no.317 
Page pp.7-12 
#Pages 6 
Date of Issue 2026-01-12 (EMM) 

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