Local alignment for query by humming

Query by humming (QBH) allows users to retrieve songs by humming a clip. In the previous work, the query has been regarded as a fragment of the music, so the task of QBH is considered to find a subsequence, which is most similar to the whole query, from the database. Taking into account humming errors, especially at the beginning or ending of the query, we assume that only part of the query is a subsequence of the music. Based on this assumption, we propose a local alignment framework which searches for the best match common subsequence between the query and database music. To verify the effectiveness of local alignment, two popular match algorithms, i.e. Linear Scaling and Dynamic Time Warping, are extended to identify the common subsequence. Experimental results on the 2010 MIREX-QBH corpus show that the new algorithms improve the retrieval accuracy significantly.