How we handle code-switching in real-time audio
A technical look at how MangoFinch detects and transcribes mid-sentence language switches in real-time multilingual meetings.
Insights on real-time transcription, multilingual communication, and AI-powered meetings.
A technical look at how MangoFinch detects and transcribes mid-sentence language switches in real-time multilingual meetings.
Step-by-step guide to using MangoFinch for real-time multilingual transcription alongside Zoom, Microsoft Teams, and Google Meet.
Our evaluation of streaming vs batch speech-to-text for real-time multilingual meeting transcription — latency, accuracy, cost, and architecture tradeoffs.
How MangoFinch preserves original language alongside translations so meeting notes stay searchable, accurate, and useful across every language.
Meeting transcription processes personal voice data. Here is what GDPR requires, where most teams get it wrong, and a practical compliance checklist.
An honest comparison of MangoFinch and Otter.ai for teams that speak multiple languages in meetings. Where each wins, and who should use which.
A technical walkthrough of the full pipeline from speech to translated text: WebSockets, streaming speech-to-text, machine translation, and the latency budget that makes it work.
Most transcription tools were built for English. Here is what actually goes wrong when your team speaks three languages in one meeting, and how we fixed it.
Best practices for getting the most accurate transcripts from your meetings.
Strategies for running effective meetings across languages and cultures.
How AI is changing business communication, from speech recognition to translation.
Making classrooms and training accessible to diverse learners.
New features, performance improvements, and language additions.
How organizations use MangoFinch to break language barriers.