I have seen image classification networks being used to classify sounds via spectrograms. It is perfectly conceivable to use ML to analyze spectrograms or to manipulate them and turn them back into sounds. Of course you can also do that directly by using time-series models.

But as long as you have a problem that can be modeled mathematically, you are usually better off to stick to mathematical models. They are usually more computationally efficient and predictable.