PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Pattern recognition algorithms for polyphonic music transcription
Antonio Pertusa and José Manuel Iñesta
In: Pattern Recognition in Information Systems (2004) INSTICC Press , Portugal , pp. 80-89. ISBN 972-8865-01-5


The main area of work in computer music related to information systems is known as music information retrieval (MIR). Databases containing musical information can be classified into two main groups: those containing audio data (digitized music) and those that file symbolic data (digital music scores). The latter are much more abstract that the former ones and contain a lot of information already coded in terms of musical symbols, thus MIR algorithms are easier and more efficient when dealing with symbolic databases. The automatic extraction of the notes in a digital musical signal (automatic music transcription) permits applying symbolic processing algorithms to audio data. In this work the performance of a neural approach and a well known non parametric algorithm, like nearest neighbours, when dealing with this problem using spectral pattern identification is analyzed.

EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Information Retrieval & Textual Information Access
ID Code:747
Deposited By:José Iñesta
Deposited On:30 December 2004