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The pitch tracking of music has been researched for several decades. Several possible improvements areavailable for creating a good t-distribution, using the instantaneous robust algorithm for pitch trackingframework to perfectly detect pitch. This article shows how to detect the pitch of music utilizing an improveddetection method which applies a statistical method; this approach uses a pitch track, or a sequence offrequency bin numbers. This sequence is used to create an index that offers useful features for comparingsimilar songs. The pitch frequency spectrum is extracted using a modified instantaneous robust algorithm forpitch tracking (IRAPT) as a base combined with the statistical method. The pitch detection algorithm wasimplemented, and the percentage of performance matching in Thai classical music was assessed in order totest the accuracy of the algorithm. We used the longest common subsequence to compare the similarities inpitch sequence alignments in the music. The experimental results of this research show that the accuracy ofretrieval of Thai classical music using the t-distribution of instantaneous robust algorithm for pitch tracking(t-IRAPT) is 99.01%, and is in the top five ranking, with the shortest query sample being five seconds long.

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