A new query-by-humming system based on the score level fusion of two classifiers

作者：Nam Gi Pyo; Park Kang Ryoung^*; Park Sung Joo; Lee Soek Pil; Kim Moo Young

来源：International Journal of Communication Systems, 2012, 25(6): 717-733.

DOI：10.1002/dac.1187

• query-by-humming
• spectro-temporal autocorrelation
• dynamic time warping
• quantized binary code
• linear scaling
• score level fusion

With the widespread use of multimedia devices, such as MP3 players, the necessity of a content-based retrieval is increased, which can find the stored music even if a user does not know the title or singer of the music. Consequently, a query-by-humming (QBH) system is introduced, which provides functionality that a user can find a piece of music by humming. Although there have been many researches into QBH, there has been little done to combine more than two classifiers based on various fusion methods. Hence, we propose a new method of QBH based on the score level fusion of two classifiers. This research is novel in the following three ways as compared with previous works. First, the features of the humming data are extracted by using musical note estimation based on the spectro-temporal autocorrelation (STA). We normalize the extracted features by using the mean-shifting, median filtering, average filtering, and minmax scaling methods. Second, a pitch-based dynamic time warping (DTW) method is used as the first classifier. We use the linear scaling (LS) method with the quantized binary (QB) code of the pitch data as the second classifier. Third, through the combination of these two classifiers based on the score level by the MIN rule, the performance of QBH is much enhanced. Experimental results with the 2006 MIREX QBSH and 2009 MIR-QBSH corpus databases showed that the performance of the proposed fusion method was best compared with single classifier and other fusion methods.

• 出版日期2012-6