Speaker Diarization GitHub Repositories (2026) · Open Source Tools

Open-source speech recognition toolkit for training, inference, streaming ASR, VAD, punctuation, speaker diarization pipelines, and OpenAI-compatible/MCP serving.

On-device Speech AI for Apple Silicon

Speaker diarization in Rust with pyannote-level accuracy. 1790–5970x realtime on NVIDIA GPUs, 430–910x on Apple Silicon.

Records and transcribes online meetings. Automatically

Frontier CoreML audio models in your apps — text-to-speech, speech-to-text, voice activity detection, and speaker diarization. In Swift, powered by SOTA open source.

AI speech toolkit for Apple Silicon — ASR, TTS, speech-to-speech, VAD, and diarization powered by MLX and CoreML

very fast speech-to-text, diarization, streaming (even in CPU) with NVIDIA Parakeet in Rust

Free, on-device AI dictation and meeting notes for macOS. Sub-second dictation with Parakeet and Whisper on Apple Silicon, plus optional AI polish. EnviousMeet (Beta): record calls with no bot, get who-said-what transcripts and AI summaries on your Mac. No account, no subscription, open source. Your audio never leaves your Mac.

End-to-End Speech Processing Toolkit

Voice AI runtime. Local first transcription, speaker diarization, TTS, and voice cloning with an OpenAI compatible API.

On-device meeting transcriber for macOS — auto-records Teams/Zoom/Webex, transcribes & separates speakers locally. No cloud. Open-source alternative to Otter/Granola/Fireflies.

Real-time, local speech-to-text with streaming ASR, speaker diarization, translation, and OpenAI/Deepgram-compatible APIs.

Meeting recorder for your Mac with a live AI assistant. On-device transcription, answers from your own docs mid-call. Local-first and open source.

Open-source AI meeting notes for Mac. Records mic + system audio with no bot, transcribes on-device or via OpenAI / Deepgram / Groq, identifies speakers offline, and writes summaries that fuse your notes with the transcript. Ask your notes and get cited answers. Tauri 2 + Rust + Swift.

A speech-to-text system you can train for $25. A frozen speech encoder and a Qwen LLM joined by a small trained projector, with word timestamps, speaker diarization, a batched HTTP server, a live demo, and a free course.

On-device transcripts and summaries of your recorded phone calls. Made for GrapheneOS; nothing leaves the phone.