An effective and efficient method for query by humming system based on multi-similarity measurement fusion

Abstract

Since it is the most natural way for people to search a specific melody in large music database, query by humming/singing is attracting more and more researchers' attention in the field of content-based music information retrieval. In this task, note-based and frame-based similarity measures are two commonly used methods. However, in previous works, researchers always focus on one of the two methods alone. In this paper, we propose a novel scheme taking advantage of two different similarity measurements to improve not only the retrieval accuracy but also the retrieving speed. First, Earth Mover's Distance (EMD), which is note-based and much faster, is adopted to eliminate most unlikely candidate. Then, Dynamic Time Warping (DTW), which is frame-based and more accurate, is executed on these surviving candidates. Finally, fusion strategies of these two similarity measurements are employed to improve the performance of whole system. Experiments show our approach can achieve 92.9% accuracy on the database used in MIREX 2006 QBH contest, which is better than those systems participated in that task

Fast Query-by-Singing/Humming System That Combines Linear Scaling and Quantized Dynamic Time Warping Algorithm

“…And detail matching with the remaining candidates is performed with the remaining candidates based on local alignment with modified cost functions. Wang et al proposed the QbSH system by combining the EMD and dynamic time warping (DTW) classifiers based on the weighted SUM rule [13].…”