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• W2489039710 abstract "In this chapter we present our experience with automatic dialogue act recognition using empirical methods for exploiting lexical semantics in an unsupervised framework. Moreover, we show how automatic dialogue act annotation of human-ECA (Embodied Conversational Agent) interactions may be used as a preliminary step in conversational analysis for modeling the users’ attitudes. Experiments are presented, by exploiting corpora of English and Italian natural dialogues. In both cases the approaches employed have been conceived as general and domain-independent and may be relevant to a wide range of both human-computer and human-human interaction application domains." @default.
• W2489039710 created "2016-08-23" @default.
• W2489039710 creator A5006685038 @default.
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• W2489039710 date "2011-01-01" @default.
• W2489039710 modified "2023-10-18" @default.
• W2489039710 title "Dialogue Act Classification Exploiting Lexical Semantics" @default.
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• W2489039710 doi "https://doi.org/10.4018/978-1-60960-617-6.ch004" @default.
• W2489039710 hasPublicationYear "2011" @default.
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