Music Data Analysis - Foundations and Applications

List of contents

MUSIC AND AUDIO. Introduction. The Musical Signal - Physically and Psychologically. Musical Structures and Their Perception. Digital Signal Processing. Digital Representation of Music. Signal-level Features. METHODS. Foundations of Statistics. Optimization. Unsupervised Classification. Supervised Classification. Evaluation. Feature Processing. Feature Selection. APPLICATIONS. Transcription. Segmentation. Instrument Recognition. Chord and Harmony Recognition. Tempo Recognition. Emotions. Structuring Of Music Collections. Music Recommendation. Automatic Composition. IMPLEMENTATION. Architecture. User Interaction. Hardware.

About the author

Dietmar Jannach, Günter Rudolphm and Igor Vatolkin are affiliated with the Department of Computer Science, TU Dortmund University, Germany

Claus Weihs is affiliated with the Department of Statistics at TU Dortmund University, Germany

Product details

• Authors: Claus (Tu Dortmund University Weihs, Claus Jannach Weihs
• Assisted by: Dietmar Jannach (Editor), Jannach Dietmar (Editor), Guenter Rudolph (Editor), Rudolph Guenter (Editor), Igor Vatolkin (Editor), Vatolkin Igor (Editor), Claus Weihs (Editor), Weihs Claus (Editor)
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Hardback
• Released: 07.11.2016
• EAN: 9781498719568
• ISBN: 978-1-4987-1956-8
• No. of pages: 694
• Series: Chapman & Hall/CRC Computer Science & Data Analysis
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; Social sciences, law, business > Business > General, dictionaries; Data Mining, Music, BUSINESS & ECONOMICS / Statistics, MATHEMATICS / Probability & Statistics / General, SCIENCE / Biotechnology, computer science, Biology, life sciences, Probability & statistics, Probability and statistics, COMPUTERS / Data Science / Data Analytics