Notes on Music Information Retrieval

The Stanford CCRMA MIR 2018 Workshop has come to an end. This year's esteemed instructors included:

• Meinard Müller (Int'l Audio Laboratories Erlangen; author, Fundamentals of Music Processing)
• Brian McFee (NYU; creator, librosa).

Click here to get 20% off Fundamentals of Music Processing by Meinard Müller. Valid June 18 to July 16, 2018.

Introduction

1. About This Site (ipynb) Start here!
2. About the book Fundamentals of Music Processing with slides (ipynb)
3. About the CCRMA Workshop on Music Information Retrieval (ipynb)
4. What is MIR? (ipynb)
5. Python Basics and Dependencies (ipynb)
6. Jupyter Basics (ipynb)
7. Jupyter Audio Basics (ipynb)
8. SoX and ffmpeg (ipynb)
9. NumPy and SciPy Basics (ipynb)
10. Alphabetical Index of Terms (ipynb)

Music Representations

1. Sheet Music Representations (ipynb)
2. Symbolic Representations (ipynb)
3. Audio Representation (ipynb)
4. Tuning Systems (ipynb)
5. Understanding Audio Features through Sonification (ipynb)

Signal Analysis and Feature Extraction

1. Basic Feature Extraction (ipynb)
2. Segmentation (ipynb)
3. Energy and RMSE (ipynb)
4. Zero Crossing Rate (ipynb)
5. Fourier Transform (ipynb)
6. Short-time Fourier Transform and Spectrogram (ipynb)
7. Constant-Q Transform and Chroma (ipynb)
8. Video: Chroma Features (ipynb)
9. Magnitude Scaling (ipynb)
10. Spectral Features (ipynb)
11. Autocorrelation (ipynb)
12. Pitch Transcription Exercise (ipynb)

Rhythm, Tempo, and Beat Tracking

1. Novelty Functions (ipynb)
2. Peak Picking (ipynb)
3. Onset Detection (ipynb)
4. Onset-based Segmentation with Backtracking (ipynb)
5. Tempo Estimation (ipynb)
6. Beat Tracking (ipynb)
7. Video: Tempo and Beat Tracking (ipynb)
8. Drum Transcription using ADTLib (ipynb)

Machine Learning

1. K-Nearest Neighbor Classification (ipynb)
2. Cross Validation (ipynb)
3. Exercise: K-Nearest Neighbor Instrument Classification (ipynb)
4. K-Means Clustering (ipynb)
5. Exercise: Unsupervised Instrument Classification using K-Means (ipynb)
6. Neural Networks (ipynb)
7. Evaluation (ipynb)
8. Genre Recognition (ipynb)
9. Exercise: Genre Recognition (ipynb)

Music Synchronization

1. Dynamic Programming (ipynb)
2. Longest Common Subsequence (ipynb)
3. Dynamic Time Warping (ipynb)
4. Dynamic Time Warping Example (ipynb)

Music Structure Analysis

1. Mel-Frequency Cepstral Coefficients (ipynb)

Content-Based Audio Retrieval

1. Locality Sensitive Hashing (ipynb)

Musically Informed Audio Decomposition

1. Principal Component Analysis (ipynb)
2. Nonnegative Matrix Factorization (ipynb)
3. Harmonic-Percussive Source Separation (ipynb)
4. Exercise: Source Separation using NMF (ipynb)

Just For Fun

1. THX Logo Theme (ipynb)