AI classification of genuine laughter versus polite laughter
Emotion is central to interpersonal communication and is often disclosed by non-linguistic vocal bursts of laughter—spontaneous, semi-involuntary, even uncontrollable and insuppressible. Laughter categories (e.g., genuine delight, polite agreeableness) can provide practical insights into persons who are inarticulate or duplicitous. This research employs artificial intelligence to classify audio samples of laughter. This research identifies which “features” (and feature combinations) are efficacious and which are not.
Authors
- Jocelynn Cu
- Karen Lok Yi Wong (ORCID: https://orcid.org/0000-0002-4079-9123)
- Merlin Teodosia Suarez (ORCID: https://orcid.org/0000-0001-8997-2989)
- Hesheng Xia (ORCID: https://orcid.org/0000-0001-8087-7272)
- Yue I. Wu
Institutions
- Sichuan University (CN)
- La Salle University (US)
- De La Salle University (PH)
Publication Details
- Journal
- The Journal of the Acoustical Society of America
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1121/10.0037443
- Primary Topic
- Sentiment Analysis and Opinion Mining
- Type
- article
- Field-Weighted Citation Impact
- 0.00