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.
A scalable cover identification engine
DI BUCCIO, EMANUELE;MONTECCHIO, NICOLA;ORIO, NICOLA
2010
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.
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