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dc.contributor.authorSingh, Chetan Pratap-
dc.contributor.authorKishore Kumar, T.-
dc.date.accessioned2025-01-09T09:28:58Z-
dc.date.available2025-01-09T09:28:58Z-
dc.date.issued2015-
dc.identifier.citation10.1109/ICACCCT.2014.7019329en_US
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/2641-
dc.descriptionNITWen_US
dc.description.abstractVarious feature schemes have been proposed through acoustic study and pattern recognition research. In this paper our main intention is to investigate the performance of different rhythmic feature schemes as well as find a good rhythmic feature combination for a robust musical instrument classifier. Lots of work has been done on speech and speaker recognition. Musical instrument recognition is an important aspect of music information retrieval system. In this paper we have discussed different rhythmic features namely beat histogram, dynamic range, spectral crest facture, mean, variance. kurtosis etc.en_US
dc.language.isoenen_US
dc.publisherProceedings of 2014 IEEE International Conference on Advanced Communication, Control and Computing Technologies, ICACCCT 2014en_US
dc.subjectTimbre featuresen_US
dc.subjectHistogramen_US
dc.titleEfficient Selection of Rhythmic Features for Musical Instrument Recognitionen_US
dc.typeOtheren_US
Appears in Collections:Electronics and Communication Engineering

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