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Notes on Music Information Retrieval
Introduction
About This Site
Why MIR?
Python Basics
Getting Good at IPython
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Using Audio in IPython
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NumPy and SciPy Basics
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Chapter 1: Basic Signal Manipulation
Overview of a Basic MIR System
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Signal Representations
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Onset Detection
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Beat Tracking
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Tempo Estimation
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Exercise: Understanding Audio Features through Sonification
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Chapter 2: Feature Extraction
Basic Feature Extraction
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Zero Crossing Rate
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Spectral Features
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Mel-Frequency Cepstral Coefficients
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Pitch Transcription Exercise
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Chapter 3: Classification
K-Nearest Neighbor Classification
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Cross Validation
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Exercise: K-Nearest Neighbor Instrument Classification
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K-Means Clustering
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Exercise: Unsupervised Instrument Classification using K-Means
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Evaluation
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Chapter 4: Matrix Factorization
Principal Component Analysis
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Nonnegative Matrix Factorization
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Harmonic-Percussive Source Separation
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Exercise: Source Separation using NMF
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Classification of Separated Signals
Chapter 5: Music Fingerprinting
Locality Sensitive Hashing
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Appendix
Segmentation
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Beat Tracking in Essentia
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Spectral Features in Essentia
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Feature Extraction in Essentia
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More (work in progress)
Tonal Descriptors: Pitch and Chroma