[x1798DE]

Yes, thanks for the feedback! I wasn't planning on feeding it the entire audiobook and trying to align the whole thing (though there are other reasons you might want to do something like this) - I figured I'd use some heuristic methods to detect chapter breaks (like long silences), then try as you say partial matching to figure out which ones correspond to what chapters (or which ones correspond to chapters at all). Like I said, it was a vague plan, but when I've played around with running things through speech-to-text in the past I haven't had excellent results. I was hoping something like this (where you have the speech and the text and just want to know how they line up) would end up being much moreo accurate.

[alpe]

You are welcome.

Using a forced aligner usually improves the results a lot when compared to using an automatic speech recognition system --- because adapting the language model to your specific text prunes a lot of choices w.r.t. a generic language model which is supposed to cover any kind of text in that given language.

Anyway, if you feed aeneas an audio file < 2 hours, 4 GB of RAM should suffice, and the default parameters should be good as well. If you just need to recognize the splits doing a full alignment is an overkill, but I guess you will happy to "waste" 5 minutes of computation time instead of spending more time implementing your own code.