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Paper Abstract and Keywords
Presentation 2024-03-01 10:40
Speech representation based on VAE assuming gamma distribution for latent variables and observation
Nanako Imaichi, Toru Nakashika (UEC) EA2023-104 SIP2023-151 SP2023-86
Abstract (in Japanese) (See Japanese page) 
(in English) Recently, deep generative models that can represent complex relationships in data generation have been attracting attention, and VAE is an example of such a model. However, since the amplitude spectrum suitable for VAE input features is always positive, a Gaussian distribution that also takes negative values into account is not appropriate. Therefore, we conducted an experiment to compare the accuracy of reconstruction by assuming a gamma distribution, a probability distribution that considers only positive values. As a result, we found that the VAE assuming the gamma distribution gave better accuracy results than the normal VAE, indicating that the gamma distribution is suitable for modeling amplitude spectra using VAE.
Keyword (in Japanese) (See Japanese page) 
(in English) deep Generative Model / VAE / amplitude spectrum representation / speech coding / gamma distribution / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 403, SP2023-86, pp. 256-261, Feb. 2024.
Paper # SP2023-86 
Date of Issue 2024-02-22 (EA, SIP, 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)
Download PDF EA2023-104 SIP2023-151 SP2023-86

Conference Information
Committee SIP SP EA IPSJ-SLP  
Conference Date 2024-02-29 - 2024-03-01 
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 2024-02-SIP-SP-EA-SLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Speech representation based on VAE assuming gamma distribution for latent variables and observation 
Sub Title (in English)  
Keyword(1) deep Generative Model  
Keyword(2) VAE  
Keyword(3) amplitude spectrum representation  
Keyword(4) speech coding  
Keyword(5) gamma distribution  
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Keyword(8)  
1st Author's Name Nanako Imaichi  
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 2024-03-01 10:40:00 
Presentation Time 60 minutes 
Registration for SP 
Paper # EA2023-104, SIP2023-151, SP2023-86 
Volume (vol) vol.123 
Number (no) no.401(EA), no.402(SIP), no.403(SP) 
Page pp.256-261 
#Pages 6 
Date of Issue 2024-02-22 (EA, SIP, SP) 

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