Indexing Music in Movies Using Audio Fingerprinting: An Audioneex Study
C.J. Wever (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Cynthia Liem – Mentor (TU Delft - Multimedia Computing)
Jeahun Kim – Mentor (TU Delft - Multimedia Computing)
J.H. Krijthe – Graduation committee member (TU Delft - Pattern Recognition and Bioinformatics)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
Music indexing, the practice of identifying songs contained in an audio sample, is an approach that is widely used. As an underlying technique, "audio fingerprinting" can be used. In this technique, an audio sample is converted to a fingerprint; a smaller representation of the audio. This fingerprint is compared to a database of fingerprinted songs in order to retrieve the original song. In this research, we aim to answer the question of how music in movies can be identified using an audio fingerprinting platform called Audioneex. Two configurable parameters in the framework have been varied, of which the configurations have been evaluated in terms of a benchmark that has been established on synthesized data. The best performing configuration found in the limits of the parameters has been compared to the base configuration of Audioneex. Based on the results, the selected configuration improved the performance of the Audioneex framework by 1 match for one matching algorithm and by 3 matches for the other available matching algorithm.