articleIEEE Transactions on Speech and Audio ProcessingFeb 22, 2005Closed access

Toward detecting emotions in spoken dialogs

University of Southern California

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Abstract

The importance of automatically recognizing emotions from human speech has grown with the increasing role of spoken language interfaces in human-computer interaction applications. This paper explores the detection of domain-specific emotions using language and discourse information in conjunction with acoustic correlates of emotion in speech signals. The specific focus is on a case study of detecting negative and non-negative emotions using spoken language data obtained from a call center application. Most previous studies in emotion recognition have used only the acoustic information contained in speech. In this paper, a combination of three sources of information-acoustic, lexical, and discourse-is used for…

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Authors

2

Topics & keywords

Keywords
  • Salience (neuroscience)
  • Computer science
  • Speech recognition
  • Classifier (UML)
  • Feature selection
  • Natural language processing
  • Artificial intelligence
  • Mutual information
UN Sustainable Development Goals
  • Reduced inequalities
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