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A Query-by-Humming System based on Marsyas Framework and GPU Acceleration Algorithms |
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PP: 261-272 |
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Author(s) |
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Li Ruan,
Long Wang,
LiMin Xiao,
MingFa Zhu,
YiLei Wu,
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Abstract |
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| Query-by-humming(QBH) is a content-based music retrieval method and represents the trend of the next-generation search
engine. Existing QBH systems still have the problems that most of the retrieval algorithms are of slower searching speeds than the
traditional query-by-text ones; lacks a practical QBH system based on the Masyas framework and the GPU acceleration algorithms. This
paper introduces a query-by-humming system which is based on the Marsyas framework and GPU acceleration algorithms. The system
design, the humming retrieval process, the humming signal feature extraction, the melody libraries establishment and corresponding
retrieval algorithms, the GPU parallel speed-up algorithms, and the experiments are presented in detail. The experimental results
verify the functionality and good performance of the proposed methods by the speedup of more than 10X with our GPU acceleration
algorithms. |
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