Audio identification based on data structure
Abstract:
Example systems and methods represent audio using a sequence of two-dimensional (2D) Fourier transforms (2DFTs), and such a sequence may be used by a specially configured machine to perform audio identification, such as for cover song identification. Such systems and methods are robust to timbral changes, time skews, and pitch skews. In particular, a special data structure provides a time-series representation of audio, and this time-series representation is robust to key changes, timbral changes, and small local tempo deviations. Accordingly, the systems and methods described herein analyze cross-similarity between these time-series representations. In some example embodiments, such systems and methods extract features from an audio fingerprint and calculate a distance measure that is robust and invariant to changes in musical structure.
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