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MDMS : Music Data Matching System for Query Variant Retrieval

Title data

Roy, Rinita ; Mayer, Ruben ; Jacobsen, Hans-Arno:
MDMS : Music Data Matching System for Query Variant Retrieval.
In: Proceedings of the 29th ACM International Conference on Multimedia. - New York : Association for Computing Machinery , 2021 . - pp. 2762-2764
ISBN 978-1-4503-8651-7
DOI: https://doi.org/10.1145/3474085.3478551

Abstract in another language

The distribution of royalty fees to music right holders is slow and inefficient due to the lack of automation in music recognition and music licensing processes. The challenge for an improved system is to recognise different versions of a music such as remix or cover versions, leading to clear assessment and unique identification of each music work. Through our music data matching system called MDMS, we query many indexed and stored music pieces with a small part of a music piece. The system retrieves the closest stored variant of the input query by using music fingerprints of the underlying melody together with signal processing techniques. Tailored indices based on fingerprint hashes accelerate processing across a large corpus of stored music. Results are found even if the stored versions vary from the query song in terms of one or more music features --- tempo, key/mode, presence of instruments/vocals, and singer --- and the differences are highlighted in the output.

Further data

Item Type: Article in a book
Refereed: Yes
Institutions of the University: Faculties
Faculties > Faculty of Mathematics, Physics und Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Data Systems
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Data Systems > Chair Data Systems - Univ.-Prof. Dr. Ruben Mayer
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science
Result of work at the UBT: No
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 26 Apr 2023 11:48
Last Modified: 05 Feb 2024 07:34
URI: https://eref.uni-bayreuth.de/id/eprint/76042