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Speech Act Profiling
Contact: Dr. Judee Burgoon
Online conversation analysis and visualization
Speech act profiling is a method of analyzing and visualizing conversations and their participants according to how they go about conversing rather than what it is they talk about. Since people may deceive in any domain, it is useful to have a analysis technique that is domain independent. Speech act profiling provides a domain independent analysis of conversations by combining the concepts of speech act theory, automated speech act classification, and fuzzy logic.
Speech acts are important and technically useful since a method has been created to automatically identify them. This method uses a manually annotated corpus of conversations to train n-gram language models and a hidden Markov model, which in turn identifies the most likely sequence of speech acts in a conversation. Using the principles of fuzzy logic, the probabilities from the hidden Markov model can be taken as degrees to which an utterance belongs to a number of fuzzy sets representing the speech acts. Speech act profiling aggregates these fuzzy sets together and subtracts from them a "normal" conversation profile (created from the training corpus) to create a profile for an entire conversation. An example profile is shown below.
Speech acts are important in deception detection for two reasons. First, they are the means by which deception is transmitted; and second, they provide a mechanism for studying deception in conversations in a content independent manner. Deceptive speakers may express more uncertainty in their messages than truthtellers \cite{depaulo-meta}, and this uncertainty can be detected in the type of speech acts speakers use. For example, uncertain speakers should tend to use more opinions, maybe expressions, and questions than truthtellers do.
Click here to contact Doug Twitchell for more information on speech act profiling.
Research Findings
- Using Speech Act Theory to Model Conversations for Automated Classification and Retrieval, International Working Conference on the Language Action Perspective on Communication Modelling
