CompositeMap: a novel framework for music similarity measure

13 years 11 months ago

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With the continuing advances in data storage and communication technology, there has been an explosive growth of music information from diﬀerent application domains. As an eﬀective technique for organizing, browsing, and searching large data collections, music information retrieval is attracting more and more attention. How to measure and model the similarity between diﬀerent music items is one of the most fundamental yet challenging research problems. In this paper, we introduce a novel framework based on a multimodal and adaptive similarity measure for various applications. Distinguished from previous approaches, our system can eﬀectively combine music properties from diﬀerent aspects into a compact signature via supervised learning. In addition, an incremental Locality Sensitive Hashing algorithm has been developed to support eﬃcient retrieval processes with diﬀerent kinds of queries. Experimental results based on two large music collections reveal various advantages ...

Bingjun Zhang, Jialie Shen, Qiaoliang Xiang, Ye Wa

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