Title :
Music emotion recognition system based on improved GA-BP
Author :
Zhu, Bin ; Zhang, Kejun
Author_Institution :
Coll. of Inf. Sci. & Technol., Zhejiang Shuren Univ., Hangzhou, China
Abstract :
In this paper, we proposed music emotion recognition and exploring system based on back propagation neural network and genetic algorithm (GA-BP). For each main rhythm of the music, emotion-related features are extracted and 8 emotion labels are assigned to them, then we find the function between the label and the emotion-related features by GA-BP, BP and the classic GA. Experimental results show classifier based on GA-BP get the highest classification rate of 83.33%. Moreover, based on the definition of music emotion vector, we provided an exploring system for people to search for a song in a fuzzy way.
Keywords :
backpropagation; emotion recognition; genetic algorithms; music; neural nets; GA-BP; back propagation neural network and genetic algorithm; exploring system; fuzzy way; music emotion recognition system; Content based retrieval; Educational institutions; Emotion recognition; Evolutionary computation; Feature extraction; Genetic algorithms; Multiple signal classification; Music information retrieval; Neural networks; Rhythm; back propgation neural network; emotion recognition; evolutionary algorithm; genetic algorithm; music exploring system;
Conference_Titel :
Computer Design and Applications (ICCDA), 2010 International Conference on
Conference_Location :
Qinhuangdao
Print_ISBN :
978-1-4244-7164-5
Electronic_ISBN :
978-1-4244-7164-5
DOI :
10.1109/ICCDA.2010.5541390
