Audio Identification by Sampling Sub-fingerprints and Counting Matches

Abstract

It is challenging to retrieve audio clips from large audio datasets not only due to the high dimensionality of audio but also due to the large number of audios. Fingerprinting methods primarily focus on the use of semantic-level techniques to speed up retrieval and neglect low-level support. This paper shows that the performance of audio retrieval can be… (More)
DOI: 10.1109/TMM.2017.2723846

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