Music Data Analysis: Foundations and Applications

This book provides a comprehensive overview of music data analysis, from introductory material to advanced concepts. It covers various applications including transcription and segmentation as well as chord and harmony, instrument and tempo recognition. It also discusses the implementation aspects of music data analysis such as architecture, user interface and hardware. It is ideal for use in university classes with an interest in music data analysis. It also could be used in computer science and statistics as well as musicology.

Table of Contents

Chapter 1: Introduction

Packt I: Music and Audio
Chapter 2: The Musical Signal: Physically and Psychologically
Chapter 3: Musical Structures and Their Perception
Chapter 4: Digital Filters and Spectral Analysis
Chapter 5: Signal-Level Features
Chapter 6: Auditory Models
Chapter 7: Digital Representation of Music
Chapter 8: Music Data: Beyond the Signal Level

Packt II: Methods
Chapter 9: Statistical Methods
Chapter 10: Optimization
Chapter 11: Unsupervised Learning
Chapter 12: Supervised Classification
Chapter 13: Evaluation
Chapter 14: Feature Processing
Chapter 15: Feature Selection

Packt III: Applications
Chapter 16: Segmentation
Chapter 17: Transcription
Chapter 18: Instrument Recognition
Chapter 19: Chord Recognition
Chapter 20: Tempo Estimation
Chapter 21: Emotions
Chapter 22: Similarity-Based Organization of Music Collections
Chapter 23: Music Recommendation
Chapter 24: Automatic Composition

Packt IV: Implementation
Chapter 25: Implementation Architectures
Chapter 26: User Interaction
Chapter 27: Hardware Architectures for Music Classification