DocumentCode :
900456
Title :
Automated classification of piano-guitar notes
Author :
Fragoulis, Dimitrios ; Papaodysseus, Constantin ; Exarhos, Mihalis ; Roussopoulos, George ; Panagopoulos, Thanasis ; Kamarotos, Dimitrios
Author_Institution :
Sch. of Electr. & Comput. Eng., Nat. Tech. Univ. of Athens, Greece
Volume :
14
Issue :
3
fYear :
2006
fDate :
5/1/2006 12:00:00 AM
Firstpage :
1040
Lastpage :
1050
Abstract :
In this paper, a new decisively important factor in both the perceptual and the automated piano-guitar identification process is introduced. This factor is determined by the nontonal spectral content of a note, while it is, in practice, totally independent of the note spectrum tonal part. This conclusion and all related results are based on a number of extended acoustical experiments, performed over the full pitch range of each instrument. The notes have been recorded from six different performers each of whom played a different instrument. Next, a number of powerful criteria for the classification between guitar and piano is proposed. Using these criteria, automated classification between 754 piano and guitar test notes has been achieved with a 100% success rate.
Keywords :
acoustic signal processing; musical instruments; signal classification; automated piano-guitar identification; nontonal spectral content; piano-guitar notes classification; Automatic testing; Helium; Instruments; Multidimensional systems; Music; Neural networks; Power engineering and energy; Speech; Steady-state; Timbre; Musical instrument classification; noontonal spectrum; timbre identification; timbre recognition;
fLanguage :
English
Journal_Title :
Audio, Speech, and Language Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1558-7916
Type :
jour
DOI :
10.1109/TSA.2005.857571
Filename :
1621216
Link To Document :
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