I'm diving into audio processing and I'm trying to wrap my head around spectral subtraction. I learned there are different approaches do it based on power, magnitude, oversubtraction. My task is to perform the spectral subtraction based on the logarithmic amplitude.

My question here is:
What is the difference between magnitude spectral subtraction, logarithmic amplitude spectral subtraction, and oversubtraction?

My second question:
Which method would be more efficient for feature extraction in the context of irregular speech (noise, silence, mispronunciation...etc)


Magnitude spectral subtraction: $\ |\hat{X}_m( \omega )| = max\{|Y_m( \omega )| - E[|D_m( \omega )|],0\}$

Power spectral subtraction: $\ |\hat{X}_m( \omega )|^{2} = max\{|Y_m( \omega )|^{2} - E[|D_m( \omega )|^{2}],0\}$

Oversubtraction: $\ |\hat{X}_m( \omega )|^{2} = max\{|Y_m( \omega )|^{2} - \alpha E[|D_m( \omega )|^{2}], \beta[|D_m( \omega )|^{2}] \}$

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I couldn't find the formula for the logarithmic amplitude spectral subtraction.

Thank you all and happy, and healthy new year.

  • $\begingroup$ Thank you for reformatting. Spectral subtraction has many aspects. Would you please add references, or how you understand formulae differ? $\endgroup$ – Laurent Duval Jan 6 at 12:18
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    $\begingroup$ @LaurentDuval Thank you for your comment. I amended my post as you suggested. $\endgroup$ – lima0 Jan 6 at 14:58

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