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Signal Processing Methods for Music Transcription de Anssi Klapuri

Signal Processing Methods for Music Transcription

Editat de Anssi Klapuri, Manuel Davy
en Limba Engleză Hardback – 8 mai 2006
This book serves as an ideal starting point for newcomers and an excellent reference source for people already working in the field. Researchers and graduate students in signal processing, computer science, acoustics and music will primarily benefit from this text. It could be used as a textbook for advanced courses in music signal processing. Since it only requires a basic knowledge of signal processing, it is accessible to undergraduate students.
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Specificații

ISBN-13: 9780387306674
ISBN-10: 0387306676
Pagini: 440
Ilustrații: XII, 440 p. 124 illus.
Dimensiuni: 155 x 235 x 25 mm
Greutate: 0.77 kg
Ediția:2006
Editura: Springer Us
Colecția Springer
Locul publicării:New York, NY, United States

Public țintă

Research

Descriere

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.

Cuprins

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.

Textul de pe ultima copertă

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.
This book aims to serve as an ideal starting point for newcomers and an excellent reference source for people already working in the field. Researchers and graduate students in signal processing, computer science, acoustics and music will primarily benefit from this text. It could be used as a textbook for advanced courses in music signal processing. Since it only requires a basic knowledge of signal processing, it is accessible to undergraduate students.

Caracteristici

The first book uniting state-of-the-art research in signal processing for music transcription
Covers a range of topics and approaches discussed by international experts in the field
Contributes to the dissemination of the increasingly relevant topic of MPEG-7 standardization
Describes models for the different subtopics of music transcription, including pitch analysis, percussion transcription, source separation, instrument recognition, and music structure analysis
Comprehensive review of existing methods
Ideal starting point for newcomers and a valuable reference source for people working in the field
Includes concrete algorithms and formulas for various methods, making it easy for the reader to implement and experiment