An Environmental Sound Source Classification System Based on Mel-Frequency Cepstral Coefficients and Gaussian Mixture Models

Title
An Environmental Sound Source Classification System Based on Mel-Frequency Cepstral Coefficients and Gaussian Mixture Models
Authors
Guanghu Shen뉴옌반쾅최종석
Keywords
sound classification; MFCCs; Gaussian Mixture Models; Pattern recognition; Impulsive sound detection; Gaussian Mixture models
Issue Date
2012-05
Publisher
14th IFAC Symposium on Information Control Problems in Manufacturing
Abstract
This paper proposed a study of a sound source classification system that has been developed for detecting and identifying the detected sound events in real environments. The proposed system was based on a pattern recognition approach using Gaussian mixture models and Mel-Frequency Cepstral Coefficients (MFCCs) features. We considered eight types of basic sound sources and an external sound. To make the system robust to various types of sound sources, we designed a tree of reference sound models for classification, in which especially generated total three of GMMs for external sounds according to different characteristics of frequency distributions. The performance of the proposed system, evaluated in terms of percent classification, indicated an averaged accuracy of 91.36% for off-line test. Finally, in on-line test our proposed system also showed a good and stable performance in real environments.
URI
http://pubs.kist.re.kr/handle/201004/43772
ISSN
14746670
Appears in Collections:
KIST Publication > Conference Paper
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