21M.387 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 additional assignments. Limited to 20.
21M.387 will be offered this semester (Fall 2018). It is instructed by E. Egozy.
Lecture occurs 11:00 AM to 12:30 PM on Tuesdays and Thursdays in 24-033F.
This class counts for a total of 12 credits. This class counts as a HASS A.
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