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Detection of the Optimum Spectral Roll-off Point using Violin as a Sound Source

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2007, 12(1), pp.53-58
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

김재천 1

1안산1대학

Accredited

ABSTRACT

Feature functions were used for the classification of music. The spectral roll-off, variance, average peak level, and class were chosen to make up a feature function vector. Among these, it is the spectral roll-off function that has a low-frequency to high-frequency ratio. To find the optimal roll-off point, the roll-off points from 0.05 to 0.95 were swept. The classification success rate was monitored as the roll-off point was being changed. The data that were used for the experiments were taken from the sounds made by a modern violin and a baroque one. Their shapes and sounds are similar, but they differ slightly in sound texture. As such, the data obtained from the sounds of these two kinds of violin can be useful in finding an adequate roll-off point. The optimal roll-off point, as determined through the experiment, was 0.85. At this point, the classification success rate was 85%, which was the highest.

Citation status

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