Comparison of Features for Musical Instrument Recognition

  title={Comparison of Features for Musical Instrument Recognition},
  author={Antti J. Eronen},
Several features were compared with regard to recognition performance in a musical instrument recognition system. Both mel-frequency and linear prediction cepstral and delta cepstral coefficients were calculated. Linear prediction analysis was carried out both on a uniform and a warped frequency scale, and reflection coefficients were also used as features. The performance of earlier described features relating to the temporal development, modulation properties, brightness, and spectral… CONTINUE READING
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Publications referenced by this paper.
Showing 1-7 of 7 references

Frequency - Warped Signal Processing f Audio Applications ”

A. Härmä
J . Audio Eng . Soc . • 2000

Bark and ERB bilinear transforms

IEEE Trans. Speech and Audio Processing • 1999

Fundamentals of speech recognition

Prentice Hall signal processing series • 1993

Pitch Estimation Using Multiple Independent Time - Frequency Windows ”

A. Klapuri

Timbre perception and auditory object identifica tion

S. Handel

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