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Paper Abstract and Keywords
Presentation 2023-03-03 09:10
Study on Analysis of Amplitude and Frequency Perturbation in the Voice for Fake Audio Detection
Kai Li, Yao Wang, Minh Le Nguyen, Masato Akagi, Masashi Unoki (JAIST) EMM2022-88
Abstract (in Japanese) (See Japanese page) 
(in English) Fake audio detection (FAD) aims to detect fake speech generated by advanced voice conversion and text-to-speech technologies. Recently, the quality of synthesized speech has significantly improved due to the remarkable development of deep neural networks. However, it is still easy for humans to identify fake speech by perceiving pathological prosody in a voice. Pathological prosody is significantly related to the amplitude and frequency perturbation (AFP) in the voice and provides essential cues to identify fake speech. This paper proposed to analyze AFP differences in the voice using the jitter and shimmer features. According to the statistical analysis of AFP features, the continuous-shimmer feature (CS3) can effectively separate genuine and fake speech signals. Moreover, static and dynamic CS3 features were combined with a light convolutional neural network bidirectional long short-term memory (LCNN-BLSTM)-based FAD system, and experiments on datasets of the Audio Deep Synthesis Detection Challenge (ADD2022) were carried out. The results of the experiments show that both the static and dynamic shimmer features of voice can provide complementary knowledge to the traditional spectrum-based FAD systems.
Keyword (in Japanese) (See Japanese page) 
(in English) fake audio detection / prosodic feature / amplitude and frequency perturbation / jitter and shimmer / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 412, EMM2022-88, pp. 110-115, March 2023.
Paper # EMM2022-88 
Date of Issue 2023-02-23 (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)
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Conference Information
Committee EMM  
Conference Date 2023-03-02 - 2023-03-03 
Place (in Japanese) (See Japanese page) 
Place (in English) Fukue culture hall 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To EMM 
Conference Code 2023-03-EMM 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Study on Analysis of Amplitude and Frequency Perturbation in the Voice for Fake Audio Detection 
Sub Title (in English)  
Keyword(1) fake audio detection  
Keyword(2) prosodic feature  
Keyword(3) amplitude and frequency perturbation  
Keyword(4) jitter and shimmer  
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1st Author's Name Kai Li  
1st Author's Affiliation Japan Advanced Institute of Science and Technology (JAIST)
2nd Author's Name Yao Wang  
2nd Author's Affiliation Japan Advanced Institute of Science and Technology (JAIST)
3rd Author's Name Minh Le Nguyen  
3rd Author's Affiliation Japan Advanced Institute of Science and Technology (JAIST)
4th Author's Name Masato Akagi  
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 2023-03-03 09:10:00 
Presentation Time 25 minutes 
Registration for EMM 
Paper # EMM2022-88 
Volume (vol) vol.122 
Number (no) no.412 
Page pp.110-115 
#Pages 6 
Date of Issue 2023-02-23 (EMM) 

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