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Music indexing allows the finding of music excerpts among a large music catalog and the detection of duplicates. With the rise of social media, it is more and more important for music owners to detect misuse and illegal use of their music. The main difficulty of this task is the detection of music excerpts when they have been strongly modified, intentionnally or not. To deal with this issue, the presented method is based on an audio representation relevant to the music content and robust to some sound modifications. Then, using a data augmentation approach, a discriminant transformation is learnt to improve the robustness of the compact representation. Finally, a hash function is derived to allow a fast searching with a large catalog together with a robustness to bit corruption.
The access to ever-increasing super-computing facilities, combined with the availability of huge data repositories (although largely unannotated), has permitted the emergence of a significant trend with pure data-driven deep learning approa
16 novembre 2023 53 min
"Basic-pitch" is a lightweight neural network for musical instrument transcription, which supports polyphonic outputs and generalizes to a wide variety of instruments (including vocals). In this talk, we will discuss how we built and evalua
16 novembre 2023 43 min
16 novembre 2023 05 min
Music Streaming Services such as Deezer offer their users a catalog of tens of millions of songs. Navigating through such a vast catalog requires retrieving and organizing musical knowledge in an automated way using music information retrie
16 novembre 2023 01 h 04 min
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Institut de Recherche et de Coordination Acoustique/Musique
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