Hervé BREDIN

I have been meaning to add this kind of progress hook for the [online demo](https://huggingface.co/spaces/pyannote/pretrained-pipelines) but it never really reached the top of my priority list. Those are the two...

FYI, I just [released](https://huggingface.co/pyannote/speaker-diarization) a much faster/more accurate version of `pyannote.audio` speaker diarization pipeline. It still does not expose the progress of the individual steps but this is now on...

Nothing built in `pyannote` comes to mind. You'd have to postprocess the [`pyannote.core.Annotation`](http://pyannote.github.io/pyannote-core/reference.html#annotation) instance returned by the pipeline: 1. remove any segment fully contained by a larger segment ``` [------A-------]...

That is a good idea, but soundata is not the only one in town :) There is also * [lhotse](https://github.com/lhotse-speech/lhotse/tree/master/lhotse/recipes) * [torchaudio](https://pytorch.org/audio/stable/datasets.html) * [datasets](https://huggingface.co/datasets/librispeech_asr)

The difference between `rttm` and `lab` lies in the fact that * `lab` format has no `filename` field, one `lab` file can therefore contain annotations for only one audio file....

Or maybe find a way to avoid this conversion (though it would probably result in slower training because of on-the-fly m4a decoding).

Did you `pip install pyannote.db.voxceleb` ?

Thanks @hadware. Will look into this at some point...

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Thanks. Would you mind sharing a link to the _RTTM file format specification_?