Investigating the use of music features in audio-based emotion detection in laughter
Date of Publication
2013
Document Type
Bachelor's Thesis
Degree Name
Bachelor of Science in Computer Science
Subject Categories
Computer Sciences
College
College of Computer Studies
Department/Unit
Computer Science
Thesis Adviser
Jocelynn Cu
Defense Panel Member
Merlin Teodisia C. Suarez
Macaria O. Cordel, II
Abstract/Summary
Laughter is one of the pan-human expressive acts. It is a powerful affective and social signal since people very often express their emotion and regulate conversations by laughing. Current works on laughter focus on analyzing it through the use of spectral and prosodic features. The differentiating factor in this work is the use of music features. We investigate the usefulness of using music features for the analysis of laughter and discrimination of emotion. We perform different building, feature extraction and modeling and validation. All of this was geared towards determining the effectiveness of music features. Results indicate that while prosodic and spectral features are good in discriminating emotions, music features does an equal and/or even better job, showing its usefulness in this area of computing.
Abstract Format
html
Language
English
Format
Accession Number
TU18491
Shelf Location
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
Physical Description
1v. various foliations : illustrations (some colored) ; 28 cm.
Keywords
Laughter; Philippine wit and humor
Recommended Citation
Canillas, R. F., Lachica, J. G., & Sy, P. C. (2013). Investigating the use of music features in audio-based emotion detection in laughter. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/11108
