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echoscript is an audio transcription tool based on the Whisper model, providing a simple and user-friendly command-line interface (CLI) for audio transcription tasks.

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echoscript

English | 繁體中文

Turn recordings and videos into editable transcripts and subtitles, with transcription running on your own computer.

  • Upload audio/video files or paste a public YouTube link.
  • Transcribe Japanese, Chinese, English, and mixed-language recordings, with hints for names and terminology.
  • Listen, edit the text, and export TXT, SRT, VTT, or JSON.

The interface supports English and Traditional Chinese.

EchoScript transcription workspace

Install

You need Linux, an NVIDIA GPU with its driver installed, and uv. uv manages Python 3.11 for this project. The web interface is included; Node.js is not required.

Install Git and FFmpeg (Ubuntu / Debian):

sudo apt update
sudo apt install -y git ffmpeg

Clone and install:

git clone https://github.com/susuky/echoscript.git
cd echoscript
uv sync

After installation succeeds, create the local settings file:

test -e .env || cp .env.example .env
chmod 600 .env

Start

From the project directory, run:

uv run --env-file .env --no-sync python serve.py

Open http://127.0.0.1:7860, upload a recording, and start transcribing. The default model is Qwen3-ASR; its first use downloads model files and takes longer.

Press Ctrl+C to stop. Use the same command to start again.

The default settings allow access from your network and have no login. For local-only access, set ECHOSCRIPT_WEB_HOST=127.0.0.1 in .env before starting.

Command-line usage

After installation, transcribe the included sample without starting the web server:

uv run --env-file .env --no-sync echoscript transcribe This_is_an_example.mp3

The transcript appears in the terminal. Replace This_is_an_example.mp3 with your audio/video file path.

For more CLI options, other models, speaker diarization, API usage, and deployment, see the usage guide (Traditional Chinese).

About

echoscript is an audio transcription tool based on the Whisper model, providing a simple and user-friendly command-line interface (CLI) for audio transcription tasks.

Resources

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1 watching

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