LipMOOC: A Modular Synthetic MOOC for Lipreading

Snigdha Agarwal, Vinay Namboodiri, C. V. Jawahar

Research output: Chapter or section in a book/report/conference proceedingChapter in a published conference proceeding

Abstract

For people with hearing impairments, lipreading is a crucial skill, as it bridges the gap between spoken language and understanding, improving the ability to communicate effectively. However, the creation of lipreading resources is pervasive and labor-intensive, leading to a scarcity of high-quality, structured, and widely accessible educational materials. To address this, we developed LipMOOC, a Massive Open Online Course (MOOC) tailored for lipreading education. Our approach leverages synthetically generated content, reducing the dependence on human-recorded videos and building an accessible and effective learning option. Using the state-of-the-art models, we created a comprehensive lipreading course and conducted a study to evaluate its effectiveness. We statistically proved that (1) Synthetic videos can replace human-recorded videos without affecting the learning outcomes, and (2) Learner performance on a structured course, i.e., LipMOOC, is much better than a standard course. A total of 120 participants with hearing impairment and no prior lipreading experience volunteered. These results highlight the potential of AI-driven content generation and scientific instructional design.

Original languageEnglish
Title of host publicationArtificial Intelligence in Education - 26th International Conference, AIED 2025, Proceedings
EditorsAlexandra I. Cristea, Erin Walker, Yu Lu, Olga C. Santos, Seiji Isotani
Place of PublicationCham, Switzerland
PublisherSpringer
Pages179-186
Number of pages8
ISBN (Electronic)9783031984624
ISBN (Print)9783031984617
DOIs
Publication statusPublished - 21 Jul 2025
Event26th International Conference on Artificial Intelligence in Education, AIED 2025 - Palermo, Italy
Duration: 22 Jul 202526 Jul 2025

Publication series

NameLecture Notes in Computer Science
Volume15881 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference26th International Conference on Artificial Intelligence in Education, AIED 2025
Country/TerritoryItaly
CityPalermo
Period22/07/2526/07/25

Keywords

  • AI Teaching
  • Inclusion
  • Learning Pedagogy
  • MOOC

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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