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This paper presents an effective re-ranking method that uses learning-to-rank paradigms to improve the accuracy of landmark-based audio fingerprinting (AFP) for audio music retrieval. The re-ranking mechanism is invoked whenever the returned ranking from an AFP system does not have a high enough confidence measure. We propose that use of new features for re-ranking, and employ the popular learning-to-rank...
This paper presents the use of GPUs (graphic processing units) for implementing an efficient audio fingerprinting (AFP) system for audio music retrieval. Such a music retrieval system can compare a 10-second recording of exact but noisy audio clip to the database of more than 100K songs on a single PC with GPU cards. Due to the use of GPUs, we can achieve a speedup factor of 14 for audio comparison,...
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