NII Technical Report (NII-2009-001E)

Title Prediction of Misunderstanding from Gesture Patterns in Psychotherapy
Authors Masashi Inoue Ryoko Hanada Nobuhiro Furuyama
Abstract We examine the possibility of predicting the occurrence of latent misunderstandings in psychotherapeutic conversations from gestural patterns. Although most misunderstandings occurring in conversations can be easily detected from the content of superficial expressions in utterances, there are some misunderstandings that are not immediately evident from the verbal interaction. Such latent misunderstandings can only be noticed when we observe the conversation carefully; thus, they may be overlooked while the therapy is being carried out. However, if we observe the conversation multimodally, there will be some cases where we can find latent misunderstandings immediately even though the content of the utterance does not contain any clues of misunderstanding. Motivated by this assumption, we investigated the applicability of machine learning as a means of detecting misunderstanding from gestural patterns observed in the conversations. We constructed classifiers using different features taken from the gesture data. In the process, we identified the gesture features that are useful in terms of classification accuracy. Then, by using the extracted gesture features, we predicted misunderstandings that were not immediately observable from the verbal queues. In an experiment using gesture features, we found a few misunderstandings that could only be discovered by careful observation of the utterance context.
Language English
Published Feb 16, 2009
Pages 19p

NII Technical Reports
National Institute of Informatics