Automated video clipping and subtitle generation using FunASR and LLMs.
Transcribe, diarize, and clip videos using local AI speech models and LLMs.
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.
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.
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.
Leverages Paraformer and SenseVoice models for high-accuracy speech recognition and timestamp prediction.
Uses CAM++ or MOSS backends to identify speaker IDs and clip segments belonging to a specific voice.
Allows specifying custom entity names and vocabulary to improve recognition accuracy during transcription.
Provides a browser-based interface for easy deployment, interaction, and multi-segment video trimming.
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.
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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It supports Paraformer-Large, Fun-ASR-Nano, SenseVoice, and MOSS for long-form transcription.
Yes, it integrates speaker recognition models to let you target trimming by speaker ID.
ImageMagick is optional unless you are running legacy subtitle tests or custom MoviePy workflows.
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