Fundamentals of Music Processing
Analyzes recorded music in digital audio form using advanced signal processing and optimization techniques to understand higher-level musical meaning. Covers fundamental tools like windowing, feature extraction, discrete and short-time Fourier transforms, chromagrams, and onset detection. Addresses analysis methods including dynamic time warping, dynamic programming, self-similarity matrices, and matrix factorization. Explores a variety of applications, such as event classification, audio alignment, chord recognition, structural analysis, tempo and beat tracking, content-based audio retrieval, and audio decomposition. Students taking graduate version complete different assignments.
Prerequisites & course information
Same subject as 21M.387[J] Subject meets with 21M.587 Prereq: 6.3000 and 21M.051 U (Spring) 3-0-9 units. HASS-A
Sources
- Course catalogue ↗2026–2027