year 4, Issue 1 (Journal of Acoustical Engineering Society of Iran 2016)
مجله انجمن علوم صوتی ایران (مهندسی صوتیات سابق) 2016, 4(1): 1-20 |
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Borjian N, Kabir E, Seyedin S, Masehian E. Query-by-example music retrieval using genre recognition to speed up the performance . مجله انجمن علوم صوتی ایران (مهندسی صوتیات سابق) 2016; 4 (1) :1-20
URL: http://joasi.ir/article-1-76-en.html
URL: http://joasi.ir/article-1-76-en.html
Abstract: (5398 Views)
The goal of a query-by-example music information retrieval system is retrieval of the target song corresponding to user-provided example from a particular dataset. The example can be a few second piece recorded from any music source such as TV or even a noisy environment e.g. gym. In this paper, a query-by-example system for music retrieval using genre recognition is proposed whose goal is to show the effect of genre recognition to achieve the accurate and rapid performance in such systems even in presence the background noise. This system includes two basic blocks: genre recognition and matching-retrieval. A binary decision tree performs the genre recognition and matching-retrieval uses two Euclidean and Kullback-Leibler (KL) distances along with a score level based decision fusion. The proposed system is evaluated on the well-known GTZAN dataset (prepared by George Tzanetakis) and by two random groups of pure and noisy queries. The results show the accuracy of 97% and 86% for two pure and noisy query groups, respectively, in retrieval time of 525 ms with Euclidean distance. These values are 97% and 82% in retrieval time of 380 ms with KL distance.
Type of Study: Research |
Received: 2015/09/28 | Accepted: 2016/09/10 | Published: 2016/09/21
Received: 2015/09/28 | Accepted: 2016/09/10 | Published: 2016/09/21
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