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Exploiting word-level features for emotion prediction

Nicholas, G and Rotaru, M and Litman, DJ (2006) Exploiting word-level features for emotion prediction. In: UNSPECIFIED.

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Abstract

In this paper we study two techniques for combining word-level features for emotion prediction. Prior research has primarily focused on the use of turn-level features as predictors. Recently, the utility of word-level features has been highlighted but only tested on relatively small human-computer corpora. We extend over previous work by investigating the strengths and weaknesses of two different techniques for using word-level features and by using a larger corpus of human-computer dialogue. Our results confirm that the word-level pitch features fare better than the turn-level ones regardless of the combination technique. In addition, we find that each word combination technique has different strengths and weaknesses in terms of precision and recall. ©2006 IEEE.


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Details

Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Nicholas, G
Rotaru, M
Litman, DJdlitman@pitt.eduDLITMAN
Centers: University Centers > Learning Research and Development Center (LRDC)
Date: 1 December 2006
Date Type: Publication
Journal or Publication Title: 2006 IEEE ACL Spoken Language Technology Workshop, SLT 2006, Proceedings
Page Range: 110 - 113
Event Type: Conference
DOI or Unique Handle: 10.1109/slt.2006.326829
Schools and Programs: Dietrich School of Arts and Sciences > Computer Science
Dietrich School of Arts and Sciences > Intelligent Systems
Refereed: Yes
ISBN: 1424408733, 9781424408733
Date Deposited: 05 Jan 2015 15:19
Last Modified: 02 Feb 2019 15:59
URI: http://d-scholarship.pitt.edu/id/eprint/23245

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