pluja/whishper

Transcribe any audio to text, translate and edit subtitles 100% locally with a web UI. Powered by whisper models!

What it solves

Whishper provides a completely local, private way to transcribe audio and video files into text and create subtitles without relying on cloud services.

How it works

It uses a suite of components including a web-based user interface, a backend coordinator, and a transcription API powered by FasterWhisper. Users can upload files or provide URLs (via yt-dlp) for processing. For translation, it integrates with LibreTranslate, and it uses MongoDB for data storage, all running on the user's own hardware (CPU or NVIDIA GPU).

Who it’s for

Content creators, privacy-conscious users, and anyone needing a self-hosted tool for audio transcription and subtitle editing.

Highlights

  • 100% Local: All transcription, translation, and editing happen on your own machine, enabling offline use.
  • Integrated Subtitle Editor: Features tools for segment splitting, insertion, and characters-per-second (CPS) warnings.
  • Flexible Input: Supports direct file uploads and URLs from any source compatible with yt-dlp.
  • Multiple Export Formats: Transcriptions can be downloaded as TXT, JSON, VTT, or SRT.

Related

  • Project
    Blue-B/WhisperSubTranslate

    WhisperSubTranslate is a desktop app that locally transcribes video audio using whisper.cpp and then translates the subtitles either offline with Tencent’s Hy‑MT2 models or via online services like DeepL or OpenAI. It runs on Windows (portable ZIP) and can be built for Linux, supports GPU acceleration, and keeps all data on the user’s machine.

  • Project
    wendy7756/AI-Video-Transcriber

    An AI-powered tool to transcribe, summarize, and archive videos and podcasts from 30+ platforms or local files using Faster-Whisper and LLMs.

  • Project
    pmarreck/yt-transcriber

    A CLI tool that transcribes YouTube videos or local media files using Whisper, with optional AI-powered summarization and translation.

  • Project
    jasoncheng7115/jt-live-whisper

    jt‑live‑whisper is an offline‑first AI toolbox for real‑time transcription, translation, speaker diarisation and meeting summarisation. It captures system audio on macOS, Windows or Linux, runs Whisper‑based or other ASR models locally, translates with a local LLM (or offline NLLB/Argos), and can produce subtitles, transcripts and AI‑generated meeting minutes—all without any cloud API.

  • Project
    chidiwilliams/buzz

    An offline transcription and translation tool powered by OpenAI's Whisper that allows users to convert audio and video to text locally on their own hardware.