Signal Processing Methods for Music Transcription

Anssi Klapuri 1 Manuel Davy 2, 3
2 SEQUEL - Sequential Learning
LIFL - Laboratoire d'Informatique Fondamentale de Lille, LAGIS - Laboratoire d'Automatique, Génie Informatique et Signal, Inria Lille - Nord Europe
3 LAGIS-SI
LAGIS - Laboratoire d'Automatique, Génie Informatique et Signal
Abstract : Signal Processing Methods for Music Transcription is the first book dedicated to uniting research related to signal processing algorithms and models for various aspects of music transcription such as pitch analysis, rhythm analysis, percussion transcription, source separation, instrument recognition, and music structure analysis. Following a clearly structured pattern, each chapter provides a comprehensive review of the existing methods for a certain subtopic while covering the most important state-of-the-art methods in detail. The concrete algorithms and formulas are clearly defined and can be easily implemented and tested. A number of approaches are covered, including, for example, statistical methods, perceptually-motivated methods, and unsupervised learning methods. The text is enhanced by a common reference and index.
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https://hal.inria.fr/inria-00120226
Contributor : Manuel Loth <>
Submitted on : Wednesday, December 13, 2006 - 4:27:36 PM
Last modification on : Thursday, February 21, 2019 - 10:52:49 AM

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  • HAL Id : inria-00120226, version 1

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Anssi Klapuri, Manuel Davy. Signal Processing Methods for Music Transcription. Springer, pp.456, 2006, 0-387-30667-6. ⟨inria-00120226⟩

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