Hey everyone! I've been using Otter.ai for our remote team's sprint retrospectives and planning sessions, and it's been a game-changer for keeping notes. Lately, we've grown the core team to six people, and that's where my issue starts.
The speaker identification seems to struggle when more than five distinct voices are in the mix. It will often lump two teammates together or label a chunk of conversation as "Speaker 6" for long stretches, even though that person introduced themselves at the start. It makes searching the transcript later for a specific person's input really hit-or-miss.
Here’s what I’ve already tried, with mixed results:
* Making sure each participant joins the meeting individually (not from a shared device).
* Having everyone say their name clearly at the very beginning during a quiet moment.
* Training the identification by manually correcting speaker labels *during* the meeting, which is a bit disruptive.
Has anyone found a reliable workflow or setup trick for larger groups? I'm wondering about:
* Is there a best practice for audio quality (like everyone using a dedicated mic)?
* Should we be using the Otter Assistant for Zoom/Teams differently?
* Or is this simply a known limitation, and I should look at splitting into smaller breakout groups for notetaking?
I love the tool and really want to make it work for our full team. Any experiences or benchmarks compared to other transcription services with larger groups would be super helpful!
Always testing.
The name intro at the start is only a seed. Otter's model needs continuous, clear audio from each speaker to lock in.
You're on the right track with dedicated mics. Headset mics are the fix. Built-in laptop mics pick up too much room noise and bleed, which scrambles the voice signature. Get everyone on a decent headset, even a basic gaming one, and it'll cut the crosstalk.
Also, check your source audio in the Otter Assistant settings. If you're piping in meeting audio from Zoom/Teams, make sure it's set to capture "individual participant audio" and not "mixed audio". Some platforms default to a single mixed stream, which cripples speaker separation.
YAML all the things.
Good question. The headset mic advice from the other reply is key, but there's also a step many people miss in the Zoom/Teams integration settings themselves.
If you're using Otter Assistant, once you've selected "individual participant audio," you also need to check that your video conferencing app isn't applying noise suppression or "high fidelity music mode" to your output. Those filters can smooth out the unique voice frequencies Otter uses to tell people apart. Try turning those off in your conferencing app's audio settings and see if the speaker separation gets more stable after a few minutes.