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Paper Abstract and Keywords
Presentation 2026-06-06 13:00
Comparative Study of Alignment Methods for Speech Synthesis from EEG
Tomohisa Sakaguchi, Tomoaki Mizuno, Toru Nakashika (UEC) SP2026-28
Abstract (in Japanese) (See Japanese page) 
(in English) Recent advances in deep learning-based speech synthesis have stimulated research on synthesizing speech from electroencephalography (EEG) signals. However, EEG is characterized by low spatial resolution and high noise levels, which cause cross-attention to diffuse and make learning temporal correspondences difficult. To address this, introducing hard alignment with monotonic constraints on attention is considered effective, but the application of hard alignment to EEG-based synthesis has not been explored. In this study, we propose two-stage learning approaches that apply Monotonic Alignment Search (MAS) to the Voice Transformer Network (VTN), aimed at stabilizing temporal alignment between EEG and acoustic features. We also incorporate Weighted Soft Alignment Search (WSAS), which converts the hard alignments obtained by MAS into Gaussian soft alignments and applies them as a bias to the attention scores, and conduct comparative experiments under multiple conditions. The results show that MAS+WSAS outperforms other conditions in PER and PSMR, suggesting that prior convergence via hard alignment serves as a guide for soft attention.
Keyword (in Japanese) (See Japanese page) 
(in English) Electroencephalography / Speech Synthesis / Hard Alignment / Brain-Machine Interface / / / /  
Reference Info. IEICE Tech. Rep., vol. 126, no. 58, SP2026-28, pp. 154-159, June 2026.
Paper # SP2026-28 
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 SP2026-28

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) Comparative Study of Alignment Methods for Speech Synthesis from EEG 
Sub Title (in English)  
Keyword(1) Electroencephalography  
Keyword(2) Speech Synthesis  
Keyword(3) Hard Alignment  
Keyword(4) Brain-Machine Interface  
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1st Author's Name Tomohisa Sakaguchi  
1st Author's Affiliation The University of Electro-Communications (UEC)
2nd Author's Name Tomoaki Mizuno  
2nd Author's Affiliation The University of Electro-Communications (UEC)
3rd Author's Name Toru Nakashika  
3rd Author's Affiliation The University of Electro-Communications (UEC)
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Speaker Author-1 
Date Time 2026-06-06 13:00:00 
Presentation Time 180 minutes 
Registration for SP 
Paper # SP2026-28 
Volume (vol) vol.126 
Number (no) no.58 
Page pp.154-159 
#Pages 6 
Date of Issue 2026-05-29 (SP) 

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