Pre-trained models are excellent for improving audio that was originally recorded at a low sample rate or was accidentally downsampled. Part "In the Spectral Region" "Spectral domain audio superresolution" implies that superresolution is performed in the frequency domain, not the time domain. That's why Aero is considered a bandwidth-expanding model.
You will notice in the examples of the project page , that the lg and hgob have the same sampling rate.

The model can generalize if it is properly trained. To capture frequencies above 11025 Hz, consider training at a higher sample rate, such as 44100 Hz instead of 22050 Hz. Change the frequency of the existing soundtracks hr, lr, and from 22,050 Hz to 44,100 Hz (using resampy or Audacity). Then use these as the new dataset and the original uncompressed MAESTRO audio as the new dataset.prlrhr

Although the highest fundamental frequency on an 88-key piano is 4186 Hz, it is important to keep in mind that piano strings have harmonic and non-harmonic overtones that create frequencies above the fundamental: As you can see, the original maestro dataset contains overtones above 11025 Hz. Not to mention the added complexity that pianos present, since all but the lowest piano notes have multiple strings tuned to the same frequency.

Explain in simple terms Give two different versions of responses. Please separate the responses with 6 asterisk symbols: ******.
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