Print Email Facebook Twitter Performance of the Dejavu audio fingerprinting framework in music identification in movies Title Performance of the Dejavu audio fingerprinting framework in music identification in movies Author Struharová, Natália (TU Delft Electrical Engineering, Mathematics and Computer Science; TU Delft Intelligent Systems) Contributor Kim, Jaehun (mentor) Liem, C.C.S. (graduation committee) Krijthe, J.H. (graduation committee) Degree granting institution Delft University of Technology Programme Computer Science and Engineering Project CSE3000 Research Project Date 2021-07-02 Abstract Audio fingerprinting is one of the standard solutions for music identification. The underlying technique is designed to be robust to signal degradation such that music can be identified despite its presence. One of the newly emerged applications of a possibly challenging nature is music identification in movies. This paper examines the audio fingerprinting framework Dejavu by evaluating its performance against an existing benchmark created for the context of music identification in movies. The results show that Dejavu’s performance matches the expectations derived from the implementation and previous testing, and can be reconfigured to improve the performance in terms of the benchmark. Subject Audio fingerprintingMusic identificationMusic Information Retrieval To reference this document use: http://resolver.tudelft.nl/uuid:1ba40730-ad68-40b7-a593-c8dbfad3cb1a Part of collection Student theses Document type bachelor thesis Rights © 2021 Natália Struharová Files PDF Natalia_Struharova_Resear ... roject.pdf 915.18 KB Close viewer /islandora/object/uuid:1ba40730-ad68-40b7-a593-c8dbfad3cb1a/datastream/OBJ/view