WhisperLive VS cog-whisper-diarization

Compare WhisperLive vs cog-whisper-diarization and see what are their differences.

cog-whisper-diarization

Cog implementation of transcribing + diarization pipeline with Whisper & Pyannote (by thomasmol)
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WhisperLive cog-whisper-diarization
4 1
1,253 94
17.0% -
9.4 7.2
7 days ago about 2 months ago
Python Python
MIT License -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

WhisperLive

Posts with mentions or reviews of WhisperLive. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-01-29.

cog-whisper-diarization

Posts with mentions or reviews of cog-whisper-diarization. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-13.
  • Whisper: Nvidia RTX 4090 vs. M1 Pro with MLX
    10 projects | news.ycombinator.com | 13 Dec 2023
    I'll take this opportunity to ask for help: What's a good open source transcription and diarization app or work flow?

    I looked at https://github.com/thomasmol/cog-whisper-diarization and https://about.transcribee.net/ (from the people behind Audapolis) but neither work that well -- crashes, etc.

    Thank you!

What are some alternatives?

When comparing WhisperLive and cog-whisper-diarization you can also consider the following projects:

whisper-writer - πŸ’¬πŸ“ A small dictation app using OpenAI's Whisper speech recognition model.

mlx - MLX: An array framework for Apple silicon

obs-zoom-and-follow - Dynamic zoom and mouse tracking script for OBS Studio

mlx-examples - Examples in the MLX framework

gpt_chatbot - This chatbot lets you use your microphone to communicate with GPT-4. It uses the OpenAI text to speech to respond with a voice. It uses Pinecone to store long term information and retrieves it to create context. API keys for OpenAI and Pinecone required. Tested on Windows

faster-whisper - Faster Whisper transcription with CTranslate2

whisper_streaming - Whisper realtime streaming for long speech-to-text transcription and translation

gpt-voice-conversation-chatbot - Allows you to have an engaging and safely emotive spoken / CLI conversation with the AI ChatGPT / GPT-4 while giving you the option to let it remember things discussed.

WhisperFusion - WhisperFusion builds upon the capabilities of WhisperLive and WhisperSpeech to provide a seamless conversations with an AI.

PaddleSpeech - Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.

LiveWhisper - A nearly-live implementation of OpenAI's Whisper, using sounddevice. Requires existing Whisper install.