A novel melody line identification algorithm for polyphonic MIDI music

  • Authors:

  • Sudha Velusamy;Balaji Thoshkahna;K. R. Ramakrishnan

  • Affiliations:

  • Music and Audio Group(MAG), Learning systems and Multimedia Labs, Department of Electrical Engineering, Indian Institute of Science, Bangalore, India;Music and Audio Group(MAG), Learning systems and Multimedia Labs, Department of Electrical Engineering, Indian Institute of Science, Bangalore, India;Music and Audio Group(MAG), Learning systems and Multimedia Labs, Department of Electrical Engineering, Indian Institute of Science, Bangalore, India

  • Venue:
  • MMM'07 Proceedings of the 13th International conference on Multimedia Modeling - Volume Part II
  • Year:
  • 2007

  • Lyrics, music, and emotions

    EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning

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Abstract

The problem of automatic melody line identification in a MIDI file plays an important role towards taking QBH systems to the next level. We present here, a novel algorithm to identify the melody line in a polyphonic MIDI file. A note pruning and track / channel ranking method is used to identify the melody line. We use results from musicology to derive certain simple heuristics for the note pruning stage. This helps in the robustness of the algorithm, by way of discarding “spurious” notes. A ranking based on the melodic information in each track / channel enables us to choose the melody line accurately. Our algorithm makes no assumption about MIDI performer specific parameters, is simple and achieves an accuracy of 97% in identifying the melody line correctly. This algorithm is currently being used by us in a QBH system built in our lab.