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Music data analysis foundations and applications

"This textbook introduces the reader to the underlying mechanisms of automated music data analysis. Written by scientists working in different fields including physics, musicology, statistics, and computer science, it is the first self-contained book on this topic."--Page 4 of cover

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Bibliographic Details
Other Authors: Weihs, Claus (Editor), Jannach, Dietmar 1973- (Editor), Vatolkin, Igor 1980- (Editor), Rudolph, Günter (Editor)
Format: Book
Language:English
Published: Boca Raton, FL CRC Press, Taylor & Francis Group [2017]
Series:Series in computer science and data analysis
Subjects:
Musical analysis > Data processing
Data mining
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Table of Contents:
  • 1. Introduction
  • I. Music and audio. 2. The musical signal: physically and psychologically
  • 3. Musical structures and their perception
  • 4. Digital filters and spectral analysis
  • 5. Signal-level features
  • 6. Auditory models
  • 7. Digital representation of music
  • 8. Music data: beyond the signal level
  • II. Methods. 9. Statistical methods
  • 10. Optimization
  • 11. Unsupervised learning
  • 12. Supervised classification
  • 13. Evaluation
  • 14. Feature processing
  • 15. Feature selection
  • III. Applications. 16. Segmentation
  • 17. Transcription
  • 18. Instrument recognition
  • 19. Chord recognition
  • 20. Tempo estimation
  • 21. Emotions
  • 22. Similarity-based organization of music collections
  • 23. Music recommendation
  • 24. Automatic composition
  • IV. Implementation. 25. Implementation architectures
  • 26. User interaction
  • 27. Hardware architectures for music classification
  • Notation

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