Similarity searching techniques in content-based audio retrieval via hashing

With this work we study suitable indexing techniques to support efficient, content-based music retrieval in large acoustic databases. To obtain the index-based retrieval mechanism applicable to audio content, we pay the most attention to the design of Locality Sensitive Hashing (LSH) and the partial sequence comparison, and propose a fast and efficient audio retrieval framework of query-by-content. On the basis of this indexable framework, four different retrieval schemes, LSH-Dynamic Programming (DP), LSH-Sparse DP (SDP), Exact Euclidian LSH ((ELSH)-L-2)-DP, (ELSH)-L-2-SDP, are presented and estimated in order to achieve an extensive understanding of retrieval algorithms performance. The experiment results indicate that compared to other three schemes, (ELSH)-L-2-SDP exhibits best tradeoff in terms of the response time, retrieval ratio, and computation cost.