How we express and interpret emotion is deeply influenced by language, culture, and context. Yet, current affective computing approaches often rely on culturally homogeneous datasets, limiting their relevance in global applications. The MMAC workshop aims to expand the field’s horizons by bringing together interdisciplinary researchers to explore how emotion is expressed and recognized across languages, cultures, and modalities.We invite submissions that address challenges and innovations in creating inclusive, context-aware affective computing systems, grounded in psychology, linguistics, HCI, machine learning, and AI ethics. 

Topics of interest:

• Cross-cultural and Multilingual Emotion Expression
• Multimodal Emotion Recognition
• Context-aware Datasets and Annotation
• Inclusive AI

Submission Guidelines

We invite submissions of short papers (max. 5 pages; 4 pages + 1 page for references) focusing on one of the 4 key topics mentioned above. The workshop encourages both theoretical papers (establishing new directions for context- and culture-aware AI) and empirical papers (presenting new datasets, annotation frameworks, analytical methods, or computational models). 

Submissions should be double-blind, i.e., anonymous, follow the official submission guidelines from ACII2025, and clearly state which one of the four key topics they most closely align with. Each paper will be sent to at least two expert reviewers associated with relevant key areas and will have one of the organizers assigned as editor.

Accepted papers will be published in the ACII 2025 Workshop Proceedings. At least one author must register for the workshop and one conference day.

Committees

Organizing Committee

• Miao Cheng, Tohoku University
• Chi-Chun Lee (Jeremy), National Tsing Hua University
• Carlos Busso, Carnegie Mellon University
• Sotaro Kita, University of Warwick

Program committee

• Chia-huei Tseng, Tohoku University
• Monica Perusquia-Hernandez, Nara Institute of Science and Technology
• Jinyao Wu, Massachusetts Institute of Technology
• Jeng-Lin Li, Inventec Corporation
• Victor Schneider, Tohoku University