Optimized Audio Classification and Segmentation Algorithm by Using Ensemble Methods

作     者：Zahid, Saadia Hussain, Fawad Rashid, Muhammad Yousaf, Muhammad Haroon Habib, Hafiz Adnan 

作者机构：Univ Engn & Technol Taxila Dept Comp Engn Taxila 47050 Pakistan Umm Al Qura Univ Coll Comp & Informat Syst Dept Comp Engn Mecca 24382 Saudi Arabia 

出 版 物：《MATHEMATICAL PROBLEMS IN ENGINEERING》 (Math. Probl. Eng.)

年 卷 期：2015年第2015卷第1期

页      面：1-11页

核心收录：

学科分类：08[工学] 0701[理学-数学] 

基　　金：Directorate of Advanced Research and Technological Studies at University of Engineering and Technology Taxila  Pakistan 

主　　题：SEGMENTATION (Image processing) COMPUTER algorithms ENSEMBLES (Mathematics) MULTIMEDIA systems APPLICATION software 

摘      要：Audio segmentation is a basis for multimedia content analysis which is the most important and widely used application nowadays. An optimized audio classification and segmentation algorithm is presented in this paper that segments a superimposed audio stream on the basis of its content into four main audio types: pure-speech, music, environment sound, and silence. An algorithm is proposed that preserves important audio content and reduces the misclassification rate without using large amount of training data, which handles noise and is suitable for use for real-time applications. Noise in an audio stream is segmented out as environment sound. A hybrid classification approach is used, bagged support vector machines (SVMs) with artificial neural networks (ANNs). Audio stream is classified, firstly, into speech and nonspeech segment by using bagged support vector machines;nonspeech segment is further classified into music and environment sound by using artificial neural networks and lastly, speech segment is classified into silence and pure-speech segments on the basis of rule-based classifier. Minimum data is used for training classifier;ensemble methods are used for minimizing misclassification rate and approximately 98% accurate segments are obtained. A fast and efficient algorithm is designed that can be used with real-time multimedia applications.