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CCRMA Workshop on Music Information Retrieval

Table of Contents

Introduction

  1. About This Workshop
  2. Getting Good at IPython
  3. Using Audio in IPython
  4. Python Basics
  5. NumPy, SciPy, Matplotlib Basics

Day 1: Basic Signal Manipulation

  1. Segmentation
  2. Signal Representations
  3. Onset Detection
  4. Beat Tracking
  5. Exercise: Understanding Audio Features through Sonification

Day 2: Spectral Feature Extraction and Classification

  1. Spectral Features
  2. Mel-Frequency Cepstral Coefficients
  3. K-Nearest Neighbor Instrument Classification

Day 3: Unsupervised Classification

  1. K-Means Clustering
  2. Exercise: Unsupervised Instrument Classification using K-Means

Day 4: Matrix Factorization and Evaluation

  1. Nonnegative Matrix Factorization
  2. Exercise: Source Separation using NMF
  3. Classification of Separated Signals
  4. Cross Validation
  5. Evaluation

Day 5: Music Fingerprinting

  1. Locality Sensitive Hashing

More (work in progress)

  1. Tonal Descriptors: Pitch and Chroma
  2. Feature Extraction
  3. Tempo Estimation

Content source: imsparsh/stanford-mir

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