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Signal Processing Methods for Music Transcription

Signal Processing Methods for Music TranscriptionCreators: Anssi Klapuri, Manuel Davy
Publisher: Springer
Category: Book

List Price: $169.00
Buy New: $103.99
as of 9/10/2010 12:40 CDT details
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Rating: 3.5 out of 5 stars 2 reviews

Media: Hardcover
Edition: 1
Pages: 440
Number Of Items: 1
Shipping Weight (lbs): 1.7
Dimensions (in): 9.3 x 6.2 x 1

ISBN: 0387306676
Dewey Decimal Number: 780.148
EAN: 9780387306674

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Product Description

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.




Customer Reviews:
5 out of 5 stars just to offset the last review...and because it is worth it   March 22, 2010
A. Glennon (new york, ny)
1 out of 1 found this review helpful

...I'm not much of a writer...but if you are interested in MIR and you've taken graduate or advanced undergraduate linear algebra and prob and stats, this book is spectacular. It provides a good introduction to the current state of the MIR field and gets you up to speed with a number of really useful machine learning techniques.


2 out of 5 stars A book for serious mathematician   September 21, 2007
symon
1 out of 8 found this review helpful

This book for is for a serious mathematician who want to do research on music.

When reading at a glance, I thought it was for multimedia software users, but at least it shows me mathematical process of transcribing music. If you are not good at mathematic, or know very little of it, you can use it as archive for further research.

For those who need to do research on how to automatically transcribe a song through signal processing, or reverse engineering as Klapuri put it, this book is good as a starting point for use in compiling these kinds of computer software. There are lots of mathematical formulas in this book, so serious mathematic scholars may find this book useful.


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