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Paper Abstract and Keywords
Presentation 2026-06-05 14:00
[Poster Presentation] A Study on Data Augmentation for Speech Emotion Recognition Using Personality, Conversational Context and VAD Scores
Sho Yamakawa, Takiko Sasaki (Musashino Univ.) SP2026-1
Abstract (in Japanese) (See Japanese page) 
(in English) In speech emotion recognition, collecting speech data labelled with emotions is difficult, and data scarcity and class imbalance pose significant challenges. In this study, using IEMOCAP as the dataset, we generated emotional response sentences based on personality information, VAD scores, and dialogue context length using a large-scale language model. We then expanded the synthetic speech data by converting these sentences into speech via TTS. Specifically, we compared multiple conditions by varying the presence or absence of Persona and VAD, as well as the context length k, and verified the impact on the performance of the SER model based on wav2vec 2.0. The experimental results showed that performance exceeding the baseline was achieved under conditions utilising both persona and VAD, with a context length of k=1. Conversely, performance declined under conditions with increased context length or those utilising VAD alone. These results suggest that, for the generation of synthetic speech data for SER, it may be important to design conditions that combine not only emotion labels but also speaker attributes and dialogue contexts of appropriate length.
Keyword (in Japanese) (See Japanese page) 
(in English) Speech Emotion Recognition / Data Augmentation / Text To Speech / Large Language Models / Persona / VAD / /  
Reference Info. IEICE Tech. Rep., vol. 126, no. 58, SP2026-1, pp. 1-6, June 2026.
Paper # SP2026-1 
Date of Issue 2026-05-29 (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 SP2026-1

Conference Information
Committee SP IPSJ-SLP IPSJ-MUS  
Conference Date 2026-06-05 - 2026-06-06 
Place (in Japanese) (See Japanese page) 
Place (in English) The University of Electro-Communications 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SP 
Conference Code 2026-06-SP-SLP-MUS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on Data Augmentation for Speech Emotion Recognition Using Personality, Conversational Context and VAD Scores 
Sub Title (in English)  
Keyword(1) Speech Emotion Recognition  
Keyword(2) Data Augmentation  
Keyword(3) Text To Speech  
Keyword(4) Large Language Models  
Keyword(5) Persona  
Keyword(6) VAD  
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Keyword(8)  
1st Author's Name Sho Yamakawa  
1st Author's Affiliation Musashino University (Musashino Univ.)
2nd Author's Name Takiko Sasaki  
2nd Author's Affiliation Musashino University (Musashino Univ.)
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Speaker Author-1 
Date Time 2026-06-05 14:00:00 
Presentation Time 180 minutes 
Registration for SP 
Paper # SP2026-1 
Volume (vol) vol.126 
Number (no) no.58 
Page pp.1-6 
#Pages 6 
Date of Issue 2026-05-29 (SP) 

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