Title :
Efficient selection of rhythmic features for musical instrument recognition
Author :
Singh, Chetan Pratap ; Kumar, T. Kishore
Author_Institution :
Dept. of E.C.E., Nat. Inst. of Technol., Warangal, India
Abstract :
Various 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.[1].
Keywords :
information retrieval; musical instruments; pattern classification; signal classification; acoustic study; beat histogram; dynamic range; music information retrieval system; musical instrument recognition; pattern recognition research; rhythmic feature combination; rhythmic feature schemes; robust musical instrument classifier; speaker recognition; spectral crest facture; speech recognition; Conferences; Dynamic range; Feature extraction; Histograms; Instruments; Multiple signal classification; Timbre; Timbre features; histogram; rhythmic features;
Conference_Titel :
Advanced Communication Control and Computing Technologies (ICACCCT), 2014 International Conference on
Conference_Location :
Ramanathapuram
Print_ISBN :
978-1-4799-3913-8
DOI :
10.1109/ICACCCT.2014.7019329
