Title :
Speech emotion recognition for SROL database using weighted KNN algorithm
Author :
Feraru, Monica ; Zbancioc, Marius
Author_Institution :
Inst. of Comput. Sci., Iasi, Romania
Abstract :
In this study, we utilized an improved version of the classical KNN algorithm which associates to each parameter from the features vectors weights according to their performance in the classification process. We obtained the recognition percents of emotions around 65-67%, for the Romanian language, on the SROL database, which are comparable with the results for other languages, with non-professional voice database. This is the first study when the parameters are extracted on the sentence level. Until now, the analysis was made on the phoneme level.
Keywords :
audio databases; emotion recognition; natural language processing; signal classification; speech recognition; Romanian language; SROL database; classification process; features vector; nonprofessional voice database; phoneme level; sentence level; speech emotion recognition; weighted KNN algorithm; Accuracy; Classification algorithms; Databases; Emotion recognition; Feature extraction; Speech; Speech recognition; emotion recognition; prosodic features; weighted KNN;
Conference_Titel :
Electronics, Computers and Artificial Intelligence (ECAI), 2013 International Conference on
Conference_Location :
Pitesti
Print_ISBN :
978-1-4673-4935-2
DOI :
10.1109/ECAI.2013.6636198
