In this paper we propose a novel architecture for environmental sound classification. In the first section we introduce the reader to the current work in this research field. Subsequently, we explore the usage of Mel frequency cepstral coefficients (MFCCs) and MPEG7 audio features in combination with a classification method based on Gaussian mixture models (GMMs). We provide details concerning the feature extraction process as well as the recognition stage of the proposed methodology. The performance of this implementation is evaluated by setting up experimental tests in six different categories of environmental sounds (aircraft, motorcycle, car, crowd, thunder, train). The proposed method is fast because it does not require high computational resources covering therefore the needs of a real time application.
Automatic recognition of urban soundscenes / S. Ntalampiras, I. Potamitis, N. Fakotakis (STUDIES IN COMPUTATIONAL INTELLIGENCE). - In: New Directions in Intelligent Interactive Multimedia / [a cura di] G.A. Tsihrintzis, M. Virvou, R.J. Howlett, L.C. Jain. - [s.l] : Springer, 2008. - ISBN 9783540681267. - pp. 147-153 (( Intervento presentato al 1. convegno International Symposium on Intelligent Interactive Multimedia Systems and Services tenutosi a Piraeus nel 2008.
Automatic recognition of urban soundscenes
S. Ntalampiras;
2008
Abstract
In this paper we propose a novel architecture for environmental sound classification. In the first section we introduce the reader to the current work in this research field. Subsequently, we explore the usage of Mel frequency cepstral coefficients (MFCCs) and MPEG7 audio features in combination with a classification method based on Gaussian mixture models (GMMs). We provide details concerning the feature extraction process as well as the recognition stage of the proposed methodology. The performance of this implementation is evaluated by setting up experimental tests in six different categories of environmental sounds (aircraft, motorcycle, car, crowd, thunder, train). The proposed method is fast because it does not require high computational resources covering therefore the needs of a real time application.File | Dimensione | Formato | |
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