talks-reducer 0.5.1

CLI for speeding up long-form talks by removing silence

Talks Reducer

Talks Reducer shortens long-form presentations by removing silent gaps and optionally re-encoding them to smaller files. The project was renamed from jumpcutter to emphasize its focus on conference talks and screencasts.

Example

• 1h 37m, 571 MB — Original OBS video recording
• 1h 19m, 751 MB — Talks Reducer
• 1h 19m, 171 MB — Talks Reducer --small

Changelog

See CHANGELOG.md.

Install GUI (Windows, macOS)

Go to the releases page and download the appropriate artifact:

• Windows — talks-reducer-windows-0.4.0.zip

• macOS — talks-reducer.app.zip

  Troubleshooting: If launching the bundle (or running python talks_reducer/gui.py) prints macOS 26 (2600) or later required, have instead 16 (1600)!, make sure you're using a Python build that ships a modern Tk. The stock python.org 3.13.5 installer includes Tk 8.6 and has been verified to work.

When extracted on Windows the bundled talks-reducer.exe behaves like the python talks_reducer/gui.py entry point: double-clicking it launches the GUI and passing a video file path (for example via Open with… or drag-and-drop onto the executable) automatically queues that recording for processing.

Install CLI (Linux, Windows, macOS)

pip install talks-reducer

Note: FFmpeg is now bundled automatically with the package, so you don't need to install it separately. You you need, don't know actually.

The --small preset applies a 720p video scale and 128 kbps audio bitrate, making it useful for sharing talks over constrained connections. Without --small, the script aims to preserve original quality while removing silence.

Example CLI usage:

talks-reducer --small input.mp4

Speech detection

Talks Reducer now relies on its built-in volume thresholding to detect speech. Adjust --silent_threshold if you need to fine-tune when segments count as silence. Dropping the optional Silero VAD integration keeps the install lightweight and avoids pulling in PyTorch.

When CUDA-capable hardware is available the pipeline leans on GPU encoders to keep export times low, but it still runs great on CPUs.

Simple web server

Prefer a lightweight browser interface? Launch the Gradio-powered simple mode with:

talks-reducer server

This opens a local web page featuring a drag-and-drop upload zone, a Small video checkbox that mirrors the CLI preset, a live progress indicator, and automatic previews of the processed output. Once the job completes you can inspect the resulting compression ratio and download the rendered video directly from the page.

Uploading and retrieving a processed video

1. Open the printed http://localhost:<port> address (the default port is 9005).
2. Drag a video onto the Video file drop zone or click to browse and select one from disk.
3. (Optional) Enable Small video before the upload finishes to apply the 720p/128 kbps preset.
4. Wait for the progress bar and log to report completion—the interface queues work automatically after the file arrives.
5. Watch the processed preview in the Processed video player and click Download processed file to save the result locally.

Need to change where the server listens? Run talks-reducer server --host 0.0.0.0 --port 7860 (or any other port) to bind to a different address.

Automating uploads from the command line

Prefer to script uploads instead of using the browser UI? Start the server and use the bundled helper to submit a job and save the processed video locally:

python -m talks_reducer.service_client --server http://127.0.0.1:9005/ --input demo.mp4 --output output/demo_processed.mp4

The helper wraps the Gradio API exposed by server.py, waits for processing to complete, then copies the rendered file to the path you provide. Pass --small to mirror the Small video checkbox or --print-log to stream the server log after the download finishes.

Contributing

See CONTRIBUTION.md for development setup details and guidance on sharing improvements.

License

Talks Reducer is released under the MIT License. See LICENSE for the full text.