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Great question, I've not encountered it too much as I'm looking for specific stuff in the transcript based on keywords so some loss is acceptable and I don't always need the data immediately so it has not been an issue so far but what I do to alleviate this somewhat is have "stitched passes" at set intervals.

News, betting games and some shows HAVE to happen exactly at a certain time and are very rarely late so you can use these known times as checkpoints with some bias. So say I run this command `ffmpeg -i http://someexamplesite.fm/8b0hqm93yceuv -c copy -f segment -segment_time 60 -reset_timestamps 1 zip-%03d.mp3` that automatically chunks the stream into 1 minute files and I know news gets read at 1pm, I can merge everything from 10am to 1pm into say "Segment B" and then process that, you get the idea.

I also have a step in the pipeline after on the transcript after that tries to summarize what it can so any small gaps would likely be inferred as I have not noticed anything too wonky and the summaries and text I get so far have been pretty clean and good enough for my needs. Once I bench this some more however I'm sure I will have this and other interesting problems to solve, the one I'm fighting now a bit is ads that have music and fast talking.



Wow thank you for the in depth reply! That makes a lot of sense about things happening on a cadence.




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