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[AI in Practice] Gemini 3.5 Transcribe: Real-time Transcription and Speaker Diarization in a macOS Meeting Translation App

Evan Lin 2026年08月28日 23:53 1 次阅读 来源:Dev.to

Previously I have a macOS App I use myself, gemini-live-translate-macos . It uses ScreenCaptureKit to directly capture audio from a specified App, eliminating the need for virtual sound cards like BlackHole. It then sends the audio to the Gemini Live API for real-time translation, outputting Traditional Chinese subtitles while playing Chinese audio. I've written two posts about the development process: the first one was about building it from scratch using AGY CLI, and the second one was about using Claude Code to take it from "functional" to "user-friendly." The starting point for this new addition was simple: I saw a document for "Real-time Transcription" added to the Live API. Since I was already connected to the Live API, I thought adding a pure transcription mode would just be a matter of changing a few parameters. However, after checking the documentation, I realized that Google released two models with very similar names but very different capabilities at once. The specific feature I actually wanted (speaker diarization) wasn't available at all on the model I originally thought it was. Two Models with Names Differing by Only Two Words Let's lay out the differences first; this is the part I spent the most time figuring out: gemini-3.5-transcribe-live gemini-3.5-transcribe API Used Live API (WebSocket streaming) Interactions API (Standard HTTP request) Usage Scenario Transcribe while speaking Upload the whole file after recording Speaker Diarization Not supported Up to 8 speakers Word-level Timestamps Not supported Supported Audio Length 10 minutes per session 1 hour (30 mins with diarization) Smart Mode SMART available smart is mutually exclusive with diarization Interim Subtitles Has interimInputTranscription Not applicable The official documentation on the Live page's limitations section is very blunt: Speaker diarization is not supported in live streaming sessions. For speaker diarization, use the non-streaming Audio transcription endpoint. So, "seeing who

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