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AI Podcast Clipper

AI Podcast Clipper for Long-Form Podcast Video

An AI podcast clipper is a tool that turns long conversational episodes into short-form clips automatically. This page explains what that actually means in practice - the model, the workflow, and who it is built for.

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Definition

What an AI podcast clipper actually does

Three jobs that used to be three separate tools - highlight selection, vertical cropping, and captioning - collapse into one upload.

  • Reads a long-form podcast .mp4 and transcribes it word-by-word.
  • Scores conversational segments and picks 1-4 clips between 40 and 60 seconds each.
  • Renders each clip vertically with active-speaker framing and burned-in captions.
Audience

Who AI Podcast Clipper is built for

Podcast hosts
Need short-form clips to promote each episode without hiring a dedicated editor.
YouTube creators
Run long-form interview shows and want Shorts that actually pull from real moments, not template snippets.
Content teams
Manage a backlog of episodes and want a predictable pipeline instead of per-clip manual editing.
Agencies
Service multiple creator clients and need a tool that handles cropping, captioning, and selected-language output in one pass.
What is in the box

Capabilities at a glance

  • Highlight detection

    Gemini 2.5 picks Q&A moments at 40-60 seconds, not arbitrary clip lengths.

  • Word-level transcription

    WhisperX produces aligned word timings used for both captions and edit boundaries.

  • Active-speaker vertical framing

    Columbia ASD drives 1080x1920 cropping with a blurred-backdrop fallback.

  • Selectable caption language

    Each processing run exports clips with English or Korean captions based on the selected language.

  • Per-user S3 storage

    Originals and clips live in scoped prefixes accessed only via presigned URLs.

  • Dashboard review

    Status moves from queued to processing to processed without manual polling.

Frequently asked questions

What is an AI podcast clipper?
An AI podcast clipper takes a long-form podcast video, uses AI to identify the strongest highlight moments, and produces short-form clips with captions and the right aspect ratio for platforms like YouTube Shorts.
How is this different from a generic AI video editor?
AI Podcast Clipper is shaped for long-form conversation. The highlight model is tuned for Q&A density rather than action cues, and the cropping uses active-speaker detection so the host or guest stays in frame as conversation moves.
Can I use it for non-podcast video?
Technically the pipeline accepts any .mp4 up to 900 MB. Quality of highlight selection drops on non-conversational content because the model is trained to surface dialogue beats.
Does it replace a human editor?
It removes the repetitive parts - finding moments, cropping, captioning, and translating - so a human editor can focus on selection, thumbnail, and platform-specific copy.