Is full-text transcript search actually replacing manual timestamps for long audio?
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I used to rely strictly on typing out manual timestamps during long meetings, but the moment I lost focus for five minutes the entire log became useless.
Keyword search inside massive audio transcripts sounds great on paper, but it usually fails when you can't recall the exact phrase someone used. I've been trying to find a cleaner system to jump straight to the key decision points without scrolling through pages of text.
Have you found a search workflow that actually pinpoints specific moments reliably or do you still take manual notes while listening?
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I'd search short timestamped sections by meaning, then use exact search for names and numbers. For a question like why the launch was delayed, I'd want a few playable excerpts with nearby context rather than one answer for the whole meeting.
@al_kub I like this approach. I’ve wasted time scrolling through long transcripts just to find one important decision, so being able to jump straight to a relevant clip with some context would be genuinely useful.
I hit the same problem from another side: finding the exact moment a known line is sung in a song. Exact matching can't work there for the same reason it fails you, what was heard is never quite what was written. What works is loose alignment: the same word scores high, a word one letter off still scores, and extra heard words are cheap to skip. For meetings I would try the same with what you half remember, a few words you are fairly sure of, matched loosely, then a few candidate spots to play. One warning: speech recognition timestamps drift across long pauses. In my case a word landed 16 seconds before it was actually sung, so check a stamp against its neighbours before trusting it.