Searching Musical Audio Using Symbolic Queries

Finding a piece of music based on its content is a key problem in music in for music information retrieval . For example, a user may be interested in finding music based on knowledge of only a small fragment of the overall tune. In this paper, we consider the searching of musical audio using symbolic queries. We first propose a relative pitch approach for representing queries and pieces. Experiments show that this technique, while effective, works best when the whole tune is used as a query. We then present an algorithm for matching based on a pitch classes approach, using the longest common subsequence between a query and target. Experimental evaluation shows that our technique is highly effective, with a mean average precision of 0.77 on a collection of 1808 recordings. Significantly, our technique is robust for truncated queries, being able to maintain effectiveness and to retrieve correct answers whether the query fragment is taken from the beginning, middle, or end of a piece. This represents a significant reduction in the burden placed on users when formulating queries.