Signal Processing Methods for Music Transcription

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Anssi Klapuri, Manuel Davy
Springer Science & Business Media, 26/02/2007 - 440 páginas

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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Índice

Rhythm and Timbre Analysis
17
An Introduction to Statistical Signal Processing
21
Sparse Adaptive Representations for Musical Signals
65
Stephen Hainsworth
101
Unpitched Percussion Transcription
130
Automatic Classification of Pitched Musical Instrument
163
Multiple Fundamental Frequency Estimation Based
203
Auditory ModelBased Methods for Multiple Fundamental
228
Unsupervised Learning Methods for Source Separation
267
Auditory Scene Analysis in Music Signals
298
Music Scene Description
327
Singing Transcription
360
References
391
Index
429
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