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FunClip

Automated video clipping and subtitle generation using FunASR and LLMs.

FunClip: AI Video Clipping & Subtitles

Transcribe, diarize, and clip videos using local AI speech models and LLMs.

Free forever · open source · MIT
✓ Light setup✓ Browser-based✓ Real-time collaboration
7.5
ZEKAI
Precise AI video clipping tool.
Free & open source · Video
Ease of setup5
Usefulness8
Maintenance9.5
Community7.5
★ 6,331
GITHUB
Sep 2026
UPDATED
MIT
LICENSE
🛠 Don't want to self-host? We can set it up →
⚡ Quick answer

FunClip is an open-source tool that automates video clipping and subtitle generation through a local Gradio UI. It uses Alibaba's FunASR models and LLMs to let you cut videos by selecting text segments, speakers, or hotwords.

Runs on
Cross-platform
Hosting
Self-host
Languages
Python
License
MIT

What it is

The software performs speech recognition via Paraformer or SenseVoice models to generate precise timestamps and SRT subtitles. You can then click through a browser interface to extract clips based on specific words, phrases, or recognized speakers.

Who it's for

It suits video editors and content creators looking to automate transcription-based clipping locally. It does not suit users wanting a traditional timeline-based NLE without command-line setup.

Key features

FunASR Integration

Leverages Paraformer and SenseVoice models for high-accuracy speech recognition and timestamp prediction.

Speaker Diarization

Uses CAM++ or MOSS backends to identify speaker IDs and clip segments belonging to a specific voice.

Hotword Customization

Allows specifying custom entity names and vocabulary to improve recognition accuracy during transcription.

Local Gradio UI

Provides a browser-based interface for easy deployment, interaction, and multi-segment video trimming.

How to start

Up and running in 3 steps

1
Clone the FunClip repository and create a Python 3.12 virtual environment.
2
Install the required dependencies and PyTorch package for your platform.
3
Launch the local Gradio interface using python funclip/launch.py.
Real talk

Our honest verdict

What's great

  • Accurate timestamp prediction integrated into Chinese and multilingual ASR models.
  • Speaker-based clipping using built-in identification models.
  • Hotword customization for specific entity and name recognition.
  • Automatic generation of full and target segment SRT subtitles.

Where it falls short

  • Requires managing a Python virtual environment and specific PyTorch dependencies.
  • Certain model backends like MOSS require setting up external vLLM services.
  • High memory requirements for advanced models and timestamp generation.
Cost

Pricing & license

Free under its MIT licence. There are no paid hosted options mentioned in the README, so the only cost is running it on your own hardware.

Paid work

Open remote AI-training roles

874 open remote AI-training roles, updated November 15, 2026; most pay $20–$170 an hour. Zekai lists them free; the application goes to the employer’s platform.

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Questions

FAQ

What models does FunClip support for ASR?

It supports Paraformer-Large, Fun-ASR-Nano, SenseVoice, and MOSS for long-form transcription.

Can I clip videos based on a specific speaker?

Yes, it integrates speaker recognition models to let you target trimming by speaker ID.

Do I need ImageMagick installed?

ImageMagick is optional unless you are running legacy subtitle tests or custom MoviePy workflows.

Radar

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