Query by humming based on multiple spectral hashing and scaled open-end dynamic time warping

摘要

Query by humming (QBH) is to retrieve songs in the music database by using user's humming. In QBH, the huge size of a song database requires an efficient search method. Recently, local sensitive hashing (LSH) has been applied in QBH and showed its superior performance. In this paper, we propose a method for QBH which uses multiple spectral hashing (MSH) and scaled open-end dynamic time warping (SOEDTW). We construct multiple binary embedding spaces by utilizing eigenvectors obtained from spectral hashing, so we call this approach as multiple spectral hashing (MSH). We also apply an improved OEDTW method for similarity matching. The experimental results demonstrate that the proposed method can improve retrieval performance greatly.