Query-by-humming/singing of MIDI and audio files by fuzzy inference system

Music Information Retrieval (MIR) is a crucial topic in the domain of information retrieval. According to major characteristics of music, Query-by-Humming system retrieves interesting music by finding melody that contains similar or equal melody to the humming query. Basing on the designed fuzzy inference model a novel Query-by-Humming/Singing system is proposed to extract pitch contour information from WAV and MIDI files in this paper. To verify the effectiveness of the presented work, the MIREX QBSH Database is employed as our experimental database and a large amount of human vocal data is used as query to test the robustness of MIR. Then, the Longest Common Subsequence (LCS) is served as an approximate matching algorithm to identify the most related top 5 music as an evaluation standard for the system. Experimental results show that the proposed system achieves 85% accuracy in the top 5 retrievals.