GA-Based Feature Extraction for Clapping Sound Detection

Author

Olajec, Ján ; Jarina, Roman ; Kuba, Michal

Author_Institution

Dept. of Telecommun., Zilina Univ.

fYear

2006

fDate

25-27 Sept. 2006

Firstpage

21

Lastpage

25

Abstract

Automatically extracting semantic content from audio streams can be helpful in many multimedia applications. In this paper, we introduce a framework for automatic feature subspace selection from a common feature vector. The selected features build a new representation which is better suitable for a given learning task and recognition. In order to solve this problem, we propose the GA-based (genetic algorithm) method to improve the representativeness and robustness of the features generic audio recognition task

Keywords

acoustic signal detection; audio signal processing; feature extraction; genetic algorithms; signal representation; audio recognition; automatic feature subspace selection; feature extraction; genetic algorithm method; multimedia application; sound detection clapping; Explosions; Feature extraction; Genetic algorithms; Mel frequency cepstral coefficient; Neural networks; Robustness; Seminars; Space exploration; Speech analysis; Streaming media; Audio classification; audio contend analysis; feature extraction; genetic algorithm; programming;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Network Applications in Electrical Engineering, 2006. NEUREL 2006. 8th Seminar on

Conference_Location

Belgrade, Serbia & Montenegro

Print_ISBN

1-4244-0433-9

Electronic_ISBN

1-4244-0433-9

Type

conf

DOI

10.1109/NEUREL.2006.341166

Filename

4147154