DocumentCode :
3738444
Title :
Towards a level assessment system of amusement in speech signals: Amused speech components classification
Author :
Kevin El Haddad;H?seyin ?akmak;St?phane Dupont;Thierry Dutoit
Author_Institution :
TCTS lab - University of Mons, Belgium
fYear :
2015
Firstpage :
12
Lastpage :
17
Abstract :
In this paper, we expose our work on classification of smiled vowels, shaking vowels and laughter syllables. This work is part of a larger framework that aims at assessing the level of amusement in speech using only audio cues. Indeed all of these three categories occur in amused speech and are considered to express a different level of amusement. Four novel features are used to accomplish this task. With only those four features, we are able to obtain good classification results with different systems. Among the compared systems, the best one achieved 21.04% error rate, therefore an accuracy well above chance.
Keywords :
"Speech","Feature extraction","Data mining","Emotion recognition","Microphones","Mel frequency cepstral coefficient","Speech recognition"
Publisher :
ieee
Conference_Titel :
Signal Processing and Information Technology (ISSPIT), 2015 IEEE International Symposium on
Type :
conf
DOI :
10.1109/ISSPIT.2015.7394252
Filename :
7394252
Link To Document :
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