Title :
Instrument identification in polyphonic music signals based on individual partials
Author :
Barbedo, Jayme Garcia Arnal ; Tzanetakis, George
Author_Institution :
DECOM/FEEC, State Univ. of Campinas, Campinas, Brazil
Abstract :
A new approach to instrument identification based on individual partials is presented. It makes identification possible even when the concurrently played instrument sounds have a high degree of spectral overlapping. A pairwise comparison scheme which emphasizes the specific differences between each pair of instruments is used for classification. Finally, the proposed method only requires a single note from each instrument to perform the classification. If more than one partial is available the resulting multiple classification decisions can be summarized to further improve instrument identification for the whole signal. Encouraging classification results have been obtained in the identification of four instruments (saxophone, piano, violin and guitar).
Keywords :
acoustic signal processing; music; musical instruments; pattern classification; guitar; individual partials; instrument identification; instrument sound spectral overlapping; multiple classification decisions; pairwise comparison scheme; piano; polyphonic music signals; saxophone; violin; Computer science; Instruments; Interference; Learning systems; Limiting; Multiple signal classification; Proposals; Signal analysis; Signal processing; Source separation; instrument identification; pairwise comparison; partial-based classification; polyphonic musical signals;
Conference_Titel :
Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on
Conference_Location :
Dallas, TX
Print_ISBN :
978-1-4244-4295-9
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2010.5495794