Vocal communication of emotion: a review of research paradigms
Speech Communication - Special issue on speech and emotion
IEEE Intelligent Systems
Predicting student emotions in computer-human tutoring dialogues
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Making computers laugh: investigations in automatic humor recognition
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Emotions from text: machine learning for text-based emotion prediction
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
HAHAcronym: a computational humor system
ACLdemo '05 Proceedings of the ACL 2005 on Interactive poster and demonstration sessions
The Multidisciplinary Facets of Research on Humour
WILF '07 Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory
Characterizing Emotion in the Soundtrack of an Animated Film: Credible or Incredible?
ACII '07 Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction
| Hi-index | 0.00 |
We analyze humorous spoken conversations from a classic comedy television show, FRIENDS, by examining acoustic-prosodic and linguistic features and their utility in automatic humor recognition. Using a simple annotation scheme, we automatically label speaker turns in our corpus that are followed by laughs as humorous and the rest as non-humorous. Our humor-prosody analysis reveals significant differences in prosodic characteristics (such as pitch, tempo, energy etc.) of humorous and non-humorous speech, even when accounted for the gender and speaker differences. Humor recognition was carried out using standard supervised learning classifiers, and shows promising results significantly above the baseline.