Fusion for Audio-Visual Laughter Detection
Year: 2007
Type: article
Abstract: . Laughter is a highly variable signal, which can be caused by a spectrum of emotions. This makes the automatic detection of laughter a challenging, but interesting task. We perform automatic laughter detection using audio-visual data from the AMI Meeting Corpus. Audiovisual laughter detection is performed by fusing the results of separate audio and video classifiers on the decision level. This results in laughter detection with a significantly higher AUC-ROC 1 than single-modality classification. 1
Author: Boris Reuderink
Language: English
Topic: Emotion and Mood Recognition
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2137111827