Abstract
Recently, there has been considerable interest in the automated recognition of affect from written and spoken language. In this paper, we investigate how information on a speaker’s affect may be inferred from lexical features using statistical methods. Dictionaries of affect offer great promise to affect sensing since they contain information on the affective qualities of single words or phrases that may be employed to estimate the emotional tone of the corresponding dialogue turn. We investigate to what extent such information may be extracted from general-purpose dictionaries in comparison to specialized dictionaries of affect. In addition, we report on results obtained for a dictionary that was tailored to our corpus.
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Osherenko, A., André, E. (2007). Lexical Affect Sensing: Are Affect Dictionaries Necessary to Analyze Affect?. In: Paiva, A.C.R., Prada, R., Picard, R.W. (eds) Affective Computing and Intelligent Interaction. ACII 2007. Lecture Notes in Computer Science, vol 4738. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74889-2_21
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DOI: https://doi.org/10.1007/978-3-540-74889-2_21
Publisher Name: Springer, Berlin, Heidelberg
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