DocumentCode :
1885391
Title :
Eco-Environmental Sound Classification Based on Matching Pursuit and Support Vector Machine
Author :
Li, Yong ; Li, Ying
Author_Institution :
Coll. of Math. & Comput. Sci., Fuzhou Univ., Fuzhou, China
fYear :
2010
fDate :
25-26 Dec. 2010
Firstpage :
1
Lastpage :
4
Abstract :
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.
Keywords :
acoustic signal processing; audio signal processing; ecology; environmental science computing; feature extraction; pattern matching; signal classification; support vector machines; audio features; eco-environmental sound classification; feature extraction technique; matching pursuit algorithm; support vector machine; Accuracy; Classification algorithms; Feature extraction; Kernel; Matching pursuit algorithms; Mel frequency cepstral coefficient; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Engineering and Computer Science (ICIECS), 2010 2nd International Conference on
Conference_Location :
Wuhan
ISSN :
2156-7379
Print_ISBN :
978-1-4244-7939-9
Electronic_ISBN :
2156-7379
Type :
conf
DOI :
10.1109/ICIECS.2010.5677677
Filename :
5677677
Link To Document :
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