In-clip search algorithm for content-based audio retrieval

Researchers are currently more interested in searching for fragments that are similar to a query, than a total data item that is similar to a query; the search interest is for “contains”, not “is”. The paper presents an O(logn) algorithm, called the “generalized virtual node (GVN)” algorithm; the GVN algorithm is a search algorithm for data fragments that have similar contents to that of a query. An example of the use of the GVN algorithm is in the search of a database of audio recordings for a few measures of a melody. Each audio clip is transformed into characteristic features and these features are stored in a hierarchical multidimensional structure, called a “k-tree”. The k-tree is exploited to build a unified retrieval model for any types of multimedia data. The experimental results of this “in-clip” search algorithm on an audio database demonstrate a search quality is qualitatively and quantitatively acceptable, with a retrieval time faster than other algorithms, such as brute-force and partial matching