A granular approach for the analysis of monophonic audio signals

Lorcan Mcdonagh 1 Frédéric Bimbot 1 Rémi Gribonval 1
1 METISS - Speech and sound data modeling and processing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : This paper describes a method for analyzing audio signals with an adaptive ``parametric dictionary''. We use sliding frames to extract elementary signals or grains from the anal- ysis signal. We search for similarities amongst the collected grains to form classes, which we then use to derive a signal model for each class. These signal models or prototypes, are used to decompose the audio signal and compute analysis parameters for each grain. As a preliminary evaluation, we tested the method with real-life, monophonic and monaural recordings and obtained encouraging results.
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Communication dans un congrès
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2003), Apr 2003, Hong-Kong, Hong Kong SAR China. IEEE, 6, pp.VI/469--VI/472, 2003, 〈10.1109/ICASSP.2003.1201720〉
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Lorcan Mcdonagh, Frédéric Bimbot, Rémi Gribonval. A granular approach for the analysis of monophonic audio signals. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2003), Apr 2003, Hong-Kong, Hong Kong SAR China. IEEE, 6, pp.VI/469--VI/472, 2003, 〈10.1109/ICASSP.2003.1201720〉. 〈inria-00574785〉

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