Optimization of Filter Combination for Query by Humming

Abstract

In a multimedia information retrieval system, the response time to a query is crucial for user experience. For a practical QBH system, developers not only need to devise an effective method of melody match, but also need to consider the response speed to a query. Although the index-based methods can effectively reduce the latency, to meet the strict requirements in most real situations where, for example, the database contains hundreds of thousands of songs, further efforts are needed. To strike a balance between response speed and retrieval accuracy, this paper presents an optimal design for filter combination (FC) applied in a query by humming (QBH) system. In the design of FC, we first make use of a greedy algorithm to sort filters and then group filters to reduce the total number of levels of filters. To further accelerate the speed of retrieval and present results within a time limit, we adopt the dynamic programming to optimize the confidence threshold in each filter. The proposed methodology can greatly accelerate the retrieval process with the cost of sacrificing the least accuracy. A four-level filtering QBH system is evaluated on a large-scale database of 100,000 MIDI files. The experimental results demonstrate the feasibility of the proposed method.