DocumentCode :
3495248
Title :
Paganini-a music analysis and recognition program
Author :
Franklin, Daniel R. ; Chicharo, Joe F.
Author_Institution :
Sch. of Electr., Comput. & Telecommun. Eng., Wollongong Univ., NSW, Australia
Volume :
1
fYear :
1999
fDate :
1999
Firstpage :
107
Abstract :
Music is an extremely rich and complex signal. With just four consecutive single notes of equal duration, a classical guitar can produce nearly four and a half million different progressions. With the addition of chords and changes in duration, these few notes can produce an enormous number of variations. Given this complexity, it is interesting to ask the question: is it possible for a computer program to extract enough information from the audio signal alone to reconstruct the original score? This paper proposes a novel approach to this problem entitled “Paganini”, based on time-frequency analysis techniques and a neural network classifier
Keywords :
audio signal processing; music; neural nets; pattern classification; time-frequency analysis; Paganini; audio signal; music analysis; neural network classifier; original score reconstruction; recognition program; time-frequency analysis techniques; Australia; Data mining; Filters; Multiple signal classification; Narrowband; Neural networks; Rhythm; Signal processing; Telecommunication computing; Time frequency analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing and Its Applications, 1999. ISSPA '99. Proceedings of the Fifth International Symposium on
Conference_Location :
Brisbane, Qld.
Print_ISBN :
1-86435-451-8
Type :
conf
DOI :
10.1109/ISSPA.1999.818124
Filename :
818124
Link To Document :
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