It's Not You, it's Me: Detecting Flirting and its Misperception in Speed-Dates

Automatically detecting human social intentions from spoken conversation is an important task for dialogue understanding. Since the social intentions of the speaker may differ from what is perceived by the hearer, systems that analyze human conversations need to be able to extract both the perceived and the intended social meaning. We investigate this difference between intention and perception by using a spoken corpus of speed-dates in which both the speaker and the listener rated the speaker on flirtatiousness. Our flirtationdetection system uses prosodic, dialogue, and lexical features to detect a speaker's

• Type: Journal
• Year: 2009
• Where: EMNLP
• Authors: Rajesh Ranganath, Dan Jurafsky, Dan McFarland
• Keywords: EMNLP 2009, Human Social Intentions, Natural Language Processing, Social Intentions, Spoken Conversation