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Machine Learned Melody Matching Using Strictly Relative Musical Abstractions, Michael Joseph Kolta
Machine Learned Melody Matching Using Strictly Relative Musical Abstractions, Michael Joseph Kolta
Legacy Theses & Dissertations (2009 - 2024)
We implement and evaluate a machine learning approach to improve systems for searching a database of music via melodic sample. We explore symbolic and aural input queries and test our prototypes with extensive user surveys. Our main contribution is to combine the following four elements. First is to create a unique musical abstraction that accounts for both pitch and rhythm in a relative manner. Second, our system allows for approximate matching of imperfect queries via the utilization of the Smith-Waterman algorithm that was originally designed for approximate matching of molecular subsequences, such as DNA samples. Third is to design our …