Eco-Environmental Sound Classification Based on Matching Pursuit and Support Vector Machine

• Published in: 2010 2nd International Conference on Information Engineering and Computer Science pp. 1 - 4
• Main Authors: Yong Li, Ying Li
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2010
• Subjects: Accuracy; Classification algorithms; Feature extraction; Kernel; Matching pursuit algorithms; Mel frequency cepstral coefficient; Support vector machines
• ISBN: 1424479398; 9781424479399
• ISSN: 2156-7379
• DOI: 10.1109/ICIECS.2010.5677677

Research on various eco-environmental sounds is very important for people to understand a particular area. However, eco-environmental sounds have many specific properties such as the diversity, high background noise and non-stationary structure which make many traditional audio features hard to characterize them accurately. In this paper, a novel feature extraction technique based on Matching Pursuit algorithm is adopted to obtain proper features which can describe the specific properties of eco-environment sounds accurately. In order to further improve the performance of our classification system, we make use of the support vector machine to automatically classify the eco-environmental sounds into seven classes. The experimental results show that our system is effective to classify the environmental sounds quickly and accurately.