Authors:
Mahfuza Farooque
and
Susana Munoz Hernández
Affiliation:
Universidad Politécnica de Madrid (UPM), Spain
Keyword(s):
Emotion Recognition, Fuzzy Reasoning Application, Voice Speech Analysis, Fuzzy Logic.
Related
Ontology
Subjects/Areas/Topics:
Approximate Reasoning and Fuzzy Inference
;
Artificial Intelligence
;
Computational Intelligence
;
Fuzzy Image, Speech and Signal Processing, Vision and Multimedia
;
Fuzzy Systems
;
Fuzzy Systems Design, Modeling and Control
;
Soft Computing
Abstract:
In human beings relations it is very important dealing with emotions. Most people is able to deduce the emotion of one person just listening his/her speech. Voice speech characteristics can help us to identify people emotions. Emotion recognition is a very interesting field in modern science and technology but to automate it is not an easy task. Many researchers and engineers are working to recognize this prospective field but the difficulty is that emotions are not clear. They are not a crisp topic. In this paper we propose to use fuzzy reasoning for emotion recognition. We based our work in some previous studies about the specific characteristics of voice speech for each human emotion (speech rate, pitch average, intensity and voice quality). We provide a simple an useful prototype that implements emotion recognition using a fuzzy model. We have used RFuzzy (a fuzzy logic reasoner over a Prolog compiler) and we have obtained a simple and efficient prototype that is able to identif
y the emotion of a person from his/her voice speech characteristics. We are trying to recognize sadness, happiness, anger, excitement and plain emotion. We have made some experiments and we provide the results that are 90% successful in the identification of emotions. Our tool is constructive, so it can be used not only to identify emotions automatically but also to recognize the people that have an emotion through their different speeches. Our prototype analyzes an emotional speech and obtains the percentage of each emotion that is detected. So it can provide many constructive answers according to our queries demand. Our prototype is an easy tool for emotion recognition that can be modify and improved by adding new rules from speech and face analysis.
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