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. Enrollment limited.
21M.387 will be offered this semester (Fall 2019). It is instructed by E. Egozy.
Lecture occurs 12:30 PM to 2:00 PM on Mondays and Fridays in 24-033F.
This class counts for a total of 12 credits. This class counts as a HASS A.
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