Title :
ESEDA: A Tool for Enhanced Speech Emotion Detection and Analysis
Author :
Sidorova, Julia ; Badia, Toni
Abstract :
This demo paper presents a speech emotion recognition tool, based on standard supervised machine learning methods and enhanced with an additional block of classification error analysis and fixing. The fixing part incorporates two optimisations: classification decomposition and treatment of the minority class problem. Experimental results demonstrate validity of this enhancement. The presentation will show capabilities of the tool described in this paper.
Keywords :
emotion recognition; learning (artificial intelligence); speech recognition; classification decomposition; classification error analysis; enhanced speech emotion detection; fixing; speech emotion recognition tool; supervised machine learning methods; Emotion recognition; Error analysis; Feature extraction; Frequency; Handicapped aids; Machine learning; Speech analysis; Speech enhancement; Speech processing; Text processing; affective computing; speech emotion recognition;
Conference_Titel :
Automated solutions for Cross Media Content and Multi-channel Distribution, 2008. AXMEDIS '08. International Conference on
Conference_Location :
Florence
Print_ISBN :
978-0-7695-3406-0
DOI :
10.1109/AXMEDIS.2008.39
