Ah-Aloud Method to Comprehend Time-Series Emotion Observation During Gameplay: An Initial Investigation with Japanese Speakers

Emotional dimensions significantly impact user experience (UX) and are essential in assessing interactions in entertainment systems. However, relying solely on subjective post-event indicators fails to capture dynamic emotional changes during the system experience. Kawashima and Watanabe introduced the "ah-aloud" method, enabling real-time emotion observation by having participants vocalize "ah" during system experiences. However, this method remains conceptual and preliminary, lacking in specific experimental procedures, analysis methods, and utilization guidelines. Our study delineates the requirements for practical "ah-aloud" application and validates its potential for game experience assessment. Consequently, the "ah-aloud" method demonstrates the potential for observing time-series emotional changes during gameplay. Based on these findings, we deliberated its utility for system evaluation and reliability as an evaluation experiment.

Authors

Institutions

Publication Details

Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2024-10-14
DOI
https://doi.org/10.1145/3677056
Primary Topic
Emotion and Mood Recognition
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ah-Aloud Method to Comprehend Time-Series Emotion Observation During Gameplay: An Initial Investigation with Japanese Speakers

Takanori Komatsu, Keita Watanabe, Eri Takayama, Takeru Yamagishi et al.
Proceedings of the ACM on Human-Computer Interaction
Emotion and Mood Recognition
article

Ah-Aloud Method to Comprehend Time-Series Emotion Observation During Gameplay: An Initial Investigation with Japanese Speakers

Takanori Komatsu, Keita Watanabe, Eri Takayama, Takeru Yamagishi, Yuki Yasunaka, Takashi Nomaru
article en

Abstract

Emotional dimensions significantly impact user experience (UX) and are essential in assessing interactions in entertainment systems. However, relying solely on subjective post-event indicators fails to capture dynamic emotional changes during the system experience. Kawashima and Watanabe introduced the "ah-aloud" method, enabling real-time emotion observation by having participants vocalize "ah" during system experiences. However, this method remains conceptual and preliminary, lacking in specific experimental procedures, analysis methods, and utilization guidelines. Our study delineates the requirements for practical "ah-aloud" application and validates its potential for game experience assessment. Consequently, the "ah-aloud" method demonstrates the potential for observing time-series emotional changes during gameplay. Based on these findings, we deliberated its utility for system evaluation and reliability as an evaluation experiment.

Proceedings of the ACM on Human-Computer InteractionVol. 8(CHI PLAY)
Meiji University (JP)
Japan Society for the Promotion of Science
Openalex Percentile: Top 78%
Emotion and Mood Recognition
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.