Audio-fingerprints and associated indexing strategies for the purpose of large-scale audio-identification

Abstract : N this work we give a precise definition of large scale audio identification. In particular, we make a distinction between exact and approximate matching. In the first case, the goal is to match two signals coming from one same recording with different post-processings. In the second case, the goal is to match two signals that are musically similar. In light of these definitions, we conceive and evaluate different audio-fingerprint models.
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Sébastien Fenet. Audio-fingerprints and associated indexing strategies for the purpose of large-scale audio-identification. Signal and Image processing. Télécom ParisTech, 2013. English. ⟨NNT : 2013ENST0051⟩. ⟨tel-01307915⟩

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