期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2017
卷号：5
期号：6
页码：12672
DOI：10.15680/IJIRCCE.2017.0506225
出版社：S&S Publications
摘要：Music Information Retrieval (MIR) is the task of retrieving information from the music and it is thefastest growing area of music industry. Music Information Retrieval basically deals with the problems of querying andretrieving certain types of information from audio files with the help of large data set. Digital music is widely availablein different digital formats due to explosive growth of information and multimedia technologies. Thus, the managementand retrieval of such music is necessary for accessing music according to their meanings in respective songs. A lot ofresearch and study has been going on in the field of music genre classification and music mood detection in the recentyears. The basic approach of the work presented in this paper is for automatic identification of genre and mooddetection of underlying audio file by mining different audio features. BoF representation is the way to represent thecomplex and high dimensional audio data. In the bag-of-frames approach, the signal is represented as the long-termdistribution of the ‘local’(frame-based) acoustic features. An early and late temporal pooling concept of sparse codinghas been used to perform the classification tasks in more efficient way to improve the accuracy of the system.
