EASY FUZZY TOOL FOR EMOTION RECOGNITION - Prototype from Voice Speech Analysis

Mahfuza Farooque, Susana Munoz Hernández

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 identify 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.

References

  1. Guadarrama S., Munoz-Hernandez S., and Vaucheret C. (2004). Fuzzy Prolog: A new approach using soft constraints propagation. Fuzzy Sets and Systems, FSS,GS-14, volume 144,1, pages 127-150, ISSN 0165-0114.
  2. Jawarkar, N. P. and Fiete (2007). Emotion recognition using prosody features and a fuzzy min-max neural classifier. In IETE Technical Review Vol 24, No 5.
  3. Victor Pablos Ceruelo, Susana Munoz-Hernandez, Hannes Strasse. Rfuzzy Framework. In Proceedings of the Workshop on Logic Programming Environmments, WLPE 2008. 15 pages.
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Paper Citation


in Harvard Style

Farooque M. and Munoz Hernández S. (2009). EASY FUZZY TOOL FOR EMOTION RECOGNITION - Prototype from Voice Speech Analysis . In Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICFC, (IJCCI 2009) ISBN 978-989-674-014-6, pages 85-88. DOI: 10.5220/0002321700850088


in Bibtex Style

@conference{icfc09,
author={Mahfuza Farooque and Susana Munoz Hernández},
title={EASY FUZZY TOOL FOR EMOTION RECOGNITION - Prototype from Voice Speech Analysis},
booktitle={Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICFC, (IJCCI 2009)},
year={2009},
pages={85-88},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002321700850088},
isbn={978-989-674-014-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICFC, (IJCCI 2009)
TI - EASY FUZZY TOOL FOR EMOTION RECOGNITION - Prototype from Voice Speech Analysis
SN - 978-989-674-014-6
AU - Farooque M.
AU - Munoz Hernández S.
PY - 2009
SP - 85
EP - 88
DO - 10.5220/0002321700850088