Humor: Prosody Analysis and Automatic Recognition for F*R*I*E*N*D*S*

We analyze humorous spoken conversations from a classic comedy television show, FRIENDS, by examining acousticprosodic 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.

• Type: Conference
• Year: 2006
• Where: EMNLP
• Authors: Amruta Purandare, Diane J. Litman
• Keywords: Automatic Humor Recognition, EMNLP 2006, EMNLP 2007, Humor Recognition, Humorous Spoken Conversations