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Focusing on the innovative field of emotion recognition, this thesis explores techniques for analyzing speech signals to identify emotional states. It employs various features to enhance the accuracy and effectiveness of recognition systems. Conducted at the University of Stuttgart, the research contributes to the intersection of signal processing and emotional intelligence, aiming to improve human-computer interaction. The work is presented in English and reflects a high academic standard, achieving a top grade.
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Comparison of different features sets and classifiers for emotion recognition of speech, Tobias Gruber
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- Année de publication
- 2015
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