Topics / #diarization

Diarization projects on GitHub

As of , the most-starred Diarization projects on GitHub are VibeVoice (54.9K stars), meetily (31.9K stars) and Speech (18.6K stars). GitHub.Locker tracks 6 Diarization repositories with 106.5K stars combined. The fastest-growing on October 16 was meetily, with +33 stars in a day.

6Projects
106.5KStars in total
+82Stars in a day

Hot right now

Most stars gained in a day · Oct 16

The all-time top

6 projects · by stars

  1. #1 · microsoft/VibeVoice

    VibeVoice

    VibeVoice is Microsoft's family of open-source voice AI models covering text-to-speech and speech recognition: long-form multi-speaker TTS, real-time streaming TTS, and ASR built for hour-long recordings.

    54.9K
  2. #2 · Zackriya-Solutions/meetily

    meetily

    A privacy-first AI meeting assistant that captures your meetings, transcribes them in real time, and generates summaries — entirely on your own machine, with no data sent to the cloud.

    31.9K
  3. #3 · NVIDIA-NeMo/Speech

    Speech

    An open-source NVIDIA framework for building speech AI models — automatic speech recognition (ASR), text-to-speech (TTS), and speech LLMs — with pre-trained checkpoints you can customize and deploy.

    18.6K
  1. 4

    nomily-app

    706Nomily-Ai/nomily-app

    Nomily AI is a BYOK (bring-your-own-key) voice recording companion for the V05E BLE recorder, iPhone, and Apple Watch, offering ASR transcription, speaker diarization, and AI-generated summaries where you choose and pay for your own transcription and LLM providers.

  2. 5

    yapsnap

    379kouhxp/yapsnap · Python

    A command-line tool that turns any video URL or local audio/video file into a plaintext transcript, running entirely on your own CPU — no GPU, no cloud, one command.

  3. 6

    personal-assistant

    109r-ayin/personal-assistant · C++

    A memory system for an AI companion that stores conversations as structured, narrative memory and carefully decides when to bring a memory back and when to stay silent, instead of just doing retrieval. It pairs a configurable backend (ASR/LLM/embeddings) with an ESP32-S3 recording device.

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