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A spectrogram is a time-varying spectral representation (forming an image) that shows how the spectral density of a signal varies with time.

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Choosing the best measure for machine learning on a Spectrogram

I'm only so familiar with your audio terminology but in your spectrogram matrix, you could seek to maximize between-class variance over in-class variance $$r_{ij} = \frac{|\sigma_{ij}^{Talas_1,Talas_2} …
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