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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962
total citations
- FWCI
- 35.59
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- References
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Authors
2Topics & keywords
Topics
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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