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

Abstract

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
Speech
Information Retrieval & Textual Information Access
ID Code:747
Deposited By:José Iñesta
Deposited On:30 December 2004