Audio fingerprinting has been an active research field typically used for music identification. Robust audio fingerprinting\ntechnology is used to successfully perform content-based audio identification regardless of the audio signal being\nsubjected to various types of distortion. These distortions affect the time-frequency correlation relating to pitch and\nspeed changes. In this paper, experiments are done using the computer vision technique ORB (Oriented FAST and\nRotated BRIEF) for robust audio identification. Investigations are conducted for ORB, relating to its advantage of robustness\nagainst distortions including speed and pitch changes. The ORB prototype compares the features of the spectrogram\nimage query to a database of spectrogram images of the songs. For the initial experiment, a Brute-Force matcher is used\nto compare the ORB descriptors. Results show that the ORB prototype performs robustly to real-world distortions with fast,\nreliable performance against distortions such as speed and pitch which justifies the research done.
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