Signal Processing Methods for Music Transcription

Author:   Anssi Klapuri ,  Manuel Davy
Publisher:   Springer-Verlag New York Inc.
Edition:   2006 ed.
ISBN:  

9780387306674


Pages:   440
Publication Date:   09 May 2006
Format:   Hardback
Availability:   Out of print, replaced by POD   Availability explained
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Signal Processing Methods for Music Transcription


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Overview

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.

Full Product Details

Author:   Anssi Klapuri ,  Manuel Davy
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   2006 ed.
Dimensions:   Width: 15.50cm , Height: 2.50cm , Length: 23.50cm
Weight:   1.790kg
ISBN:  

9780387306674


ISBN 10:   0387306676
Pages:   440
Publication Date:   09 May 2006
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Out of print, replaced by POD   Availability explained
We will order this item for you from a manufatured on demand supplier.

Table of Contents

Foundations.- to Music Transcription.- An Introduction to Statistical Signal Processing and Spectrum Estimation.- Sparse Adaptive Representations for Musical Signals.- Rhythm and Timbre Analysis.- Beat Tracking and Musical Metre Analysis.- Unpitched Percussion Transcription.- Automatic Classification of Pitched Musical Instrument Sounds.- Multiple Fundamental Frequency Analysis.- Multiple Fundamental Frequency Estimation Based on Generative Models.- Auditory Model-Based Methods for Multiple Fundamental Frequency Estimation.- Unsupervised Learning Methods for Source Separation in Monaural Music Signals.- Entire Systems, Acoustic and Musicological Modelling.- Auditory Scene Analysis in Music Signals.- Music Scene Description.- Singing Transcription.

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