Title :
Samples-based automatic key segment extraction for popular songs
Author :
Zhang, Yi-bin ; Zhou, Jie ; Bian, Zhao-Qi
Author_Institution :
Dept. of Autom., Tsinghua Univ., Beijing, China
Abstract :
In this paper, we define the key segment of a popular song as the most impressive part in this song. It can be regarded as a perfect index or summary for this song, therefore it is much helpful for popular song´s audition and management. We propose an effective algorithm for automatic key segment extraction based on the analysis of positive and negative samples of key segment extracted manually from a training database. An experiment is carried on a test database including 130 popular songs. Compared with manually extraction of key segments, the proposed algorithm has a rather satisfying performance.
Keywords :
audio databases; entertainment; indexing; information retrieval; learning (artificial intelligence); music; digital entertainment; indexing; negative samples; neural network; popular song audition; popular song management; positive samples; samples-based automatic key segment extraction; training database; Algorithm design and analysis; Automation; Databases; Europe; Information management; Large-scale systems; Management training; Marketing and sales; Neural networks; Testing; Digital entertainment; key segment extraction; neural network; popular song;
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
DOI :
10.1109/ICMLC.2005.1527804
