A scalable cover identification engine

Authors:
Emanuele Di Buccio;Nicola Montecchio;Nicola Orio
Affiliations:
University of Padova, Padova, Italy;University of Padova, Padova, Italy;University of Padova, Padova, Italy
Venue:
Proceedings of the international conference on Multimedia
Year:
2010

Citing 5
Cited 0

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Lucene in Action (In Action series)
A Review of Audio Fingerprinting

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Using Exact Locality Sensitive Mapping to Group and Detect Audio-Based Cover Songs

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Chroma Binary Similarity and Local Alignment Applied to Cover Song Identification

IEEE Transactions on Audio, Speech, and Language Processing

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Abstract

This paper describes the implementation of a content-based cover song identification system which has been released under an open source license. The system is centered around the Apache Lucene text search engine library, and proves how classic techniques derived from textual Information Retrieval, in particular the bag-of-words paradigm, can successfully be adapted to music identification. The paper focuses on extensive experimentation on the most influential system parameters, in order to find an optimal tradeoff between retrieval accuracy and speed of querying.