Piotr Żelasko

Regarding the progress bar issues, I'm sure that such a comprehensive framework as PT Lightning has some way to support datasets that have unknown length and wouldn't force you to...

Did you check that it works with `shorten` encoded SPH? Some older LDC distributions have SPH that couldn't be opened with anything other than sph2pipe or shorten.

No, I don't think it's in the tests. You'd have to try something old like maybe Callhome, not sure but maybe also SWBD. I don't remember which corpora this happened...

I quickly compared the results between old and new whisper implementations on a 60s clip from AMI. In that clip, I noticed that faster-whisper tends to skip short, isolated, and...

Thanks! I'll review it tomorrow, but before I do -- based on your description, it looks like a similar outcome may be achieved by running the `activity_detection` workflow and then...

As a note regarding mono vs multi channel: I think it makes sense to load and process each channel separately with VAD, and assign the resulting supervision to the right...

I think this workflow can be recreated with the existing operations as follows: ```python # pseudo-code workflow recordings = RecordingSet(...) # N recordings supervisions = activity_detection(recordings) # M supervisions cuts...

I think I'm starting to understand what you are trying to achieve. Can you confirm the problem boils down to the following description: ``Given a cut with N supervisions modify...

I'm still not sure. It looks like your example may be implemented with `.truncate()/.split()` to remove the detected non-speech segments and `.append()` to combine whatever cuts remained. The issue that...

I appreciate the discussion but the design you're suggesting is too complex and not necessary. You can already achieve sequential loading of various audio chunks using cuts. If you need...