TY - GEN
T1 - Musical instrument identification using principal component analysis and multi-layered perceptrons
AU - Loughran, Róisín
AU - Walker, Jacqueline
AU - O'Neill, Michael
AU - O'Farrell, Marion
PY - 2008
Y1 - 2008
N2 - This study aims to create an automatic musical instrument classifier by extracting audio features from real sample sounds. These features are reduced using Principal Component Analysis and the resultant data is used to train a Multi-Layered Perceptron. We found that the RMS temporal envelope and the evolution of the centroid gave the most interesting results of the features studied. These results were found to be competitive whether the scope of the data was across one octave or across the range of each instrument.
AB - This study aims to create an automatic musical instrument classifier by extracting audio features from real sample sounds. These features are reduced using Principal Component Analysis and the resultant data is used to train a Multi-Layered Perceptron. We found that the RMS temporal envelope and the evolution of the centroid gave the most interesting results of the features studied. These results were found to be competitive whether the scope of the data was across one octave or across the range of each instrument.
UR - http://www.scopus.com/inward/record.url?scp=51849161598&partnerID=8YFLogxK
U2 - 10.1109/ICALIP.2008.4590236
DO - 10.1109/ICALIP.2008.4590236
M3 - Conference contribution
AN - SCOPUS:51849161598
SN - 9781424417230
T3 - ICALIP 2008 - 2008 International Conference on Audio, Language and Image Processing, Proceedings
SP - 643
EP - 648
BT - ICALIP 2008 - 2008 International Conference on Audio, Language and Image Processing, Proceedings
T2 - ICALIP 2008 - 2008 International Conference on Audio, Language and Image Processing
Y2 - 7 July 2008 through 9 July 2008
ER -