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Paper Abstract and Keywords
Presentation 2026-03-03 10:20
Unspoken Context Change: Detecting Implicit Prerequisite Shifts in Lecture Texts
Ko Fujimura (Otsuma Univ.) LOIS2025-66
Abstract (in Japanese) (See Japanese page) 
(in English) In explanatory speech and lectures, listeners may suddenly experience difficulty in understanding when the prerequisite knowledge required for comprehension shifts implicitly, even though the topic itself remains continuous. Such Unspoken Context Change—implicit shifts in assumed prerequisites—is difficult to capture using conventional topic change detection or analyses based solely on semantic similarity. In this study, we propose two approaches for detecting unspoken context change in explanatory speech using large language models (LLMs). The first approach quantitatively identifies points where prerequisite demands change while topical continuity is preserved by analyzing utterance-level LLM embedding vectors over time. The second approach directly infers unspoken context change through prompt-based reasoning with an LLM. We implement both approaches and conduct experiments on subtitle transcripts of lecture videos, demonstrating that unspoken context change can be detected from explanatory speech. These methods have the potential to serve as speaker-support tools in future face-to-face and live online lectures.
Keyword (in Japanese) (See Japanese page) 
(in English) LLM / embedding model / text mining / lecture text / unspoken context change / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 375, LOIS2025-66, pp. 102-107, March 2026.
Paper # LOIS2025-66 
Date of Issue 2026-02-23 (LOIS) 
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 LOIS  
Conference Date 2026-03-02 - 2026-03-03 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
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Paper Information
Registration To LOIS 
Conference Code 2026-03-LOIS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Unspoken Context Change: Detecting Implicit Prerequisite Shifts in Lecture Texts 
Sub Title (in English)  
Keyword(1) LLM  
Keyword(2) embedding model  
Keyword(3) text mining  
Keyword(4) lecture text  
Keyword(5) unspoken context change  
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1st Author's Name Ko Fujimura  
1st Author's Affiliation Otsuma Women's University (Otsuma Univ.)
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Speaker Author-1 
Date Time 2026-03-03 10:20:00 
Presentation Time 25 minutes 
Registration for LOIS 
Paper # LOIS2025-66 
Volume (vol) vol.125 
Number (no) no.375 
Page pp.102-107 
#Pages 6 
Date of Issue 2026-02-23 (LOIS) 

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