Turn Interviews Into Clips Automatically - OpenClip
Interview to Clips

Turn Interviews Into Highlight Clips Automatically

The best interview moments are answers, not timestamps — and clipping them means handling two faces, one frame, and a conversation that moves. OpenClip finds the strongest exchanges, cuts the vertical frame between speakers, and captions everything automatically.

content-repurposing
starter

Scenario

Interview footage is uniquely awkward to clip. The content structure is question-and-answer, so a good clip needs the setup and the payoff — cut the question and the answer floats context-free; keep too much and the clip drags. The visual structure is worse: a two-shot, alternating cameras, or a remote call layout, all of which collapse under a naive vertical crop that either shows two half-faces or locks onto whoever isn't talking. This is why interview highlights have traditionally required a human editor who understands the conversation. OpenClip replicates that judgment mechanically: speaker diarization maps every question and answer, moment detection scores exchanges for quotability and emotional register, and face tracking cuts the 9:16 frame to the active speaker — question framed on the interviewer, answer framed on the guest — with word-level captions burned in. Works the same for a media interview, a customer story session, a hiring panel, or a documentary sit-down.

Workflow

1

Upload the interview footage

Submit any interview recording — a two-camera studio edit, a single wide shot, or a remote call from Zoom or Riverside. Multi-hour raw footage is fine; the AI does the sifting.

2

AI maps questions and answers

Speaker diarization separates interviewer from subject and segments the conversation into exchange units — so clips are built from complete Q&A pairs, not arbitrary in-and-out points.

3

The strongest answers surface

Each exchange is scored for hook, specificity, and emotional weight. The ranked shortlist is the same set of moments a good editor would flag on a first viewing pass.

4

Active-speaker vertical framing

Face tracking frames whoever is talking and cuts between speakers as the exchange moves — the question on the interviewer, the answer on the guest — in clean 9:16.

5

Captioned clips, ready anywhere

Word-level captions burn in with your chosen preset. Export vertical for Reels, Shorts, TikTok, and LinkedIn, or keep the original frame for embeds and press pages.

Benefits

Clips are built from complete question-answer exchanges, not blind time slices
Face tracking cuts between interviewer and guest — no two-half-faces crops
AI ranking replicates an editor's first-pass moment selection in minutes
Word-level captions make quiet, thoughtful answers work in muted feeds
Same pipeline serves media interviews, customer stories, and documentary footage
Guests get shareable clips of their own appearance — distribution multiplies

Key Metrics

5-15

Clips per interview

Multiple

Speakers tracked

2-4 hrs

First-pass edit replaced

Word-level

Caption sync

Features

Q&A-Aware Diarization

Separates interviewer from subject and segments the conversation into exchanges — the structural understanding that makes interview clips coherent.

Answer-Quality Ranking

Scores exchanges for specificity, surprise, and emotional register — surfacing the quotable answers a producer would circle in the transcript.

Two-Person Frame Switching

The 9:16 crop follows the active speaker and cuts between faces as the conversation volleys — the exact pattern editors keyframe manually for interview verticals.

Word-Level Captions

Captions sync to each word in 10 visual presets, keeping soft-spoken or accented answers fully readable in silent autoplay.

Every Destination From One Pass

Vertical exports for social feeds, original-frame exports for press pages and embeds — one detection pass covers both.

Any Interview Format

Studio two-shots, single wide angles, remote call grids, and mixed-camera edits all parse — face tracking adapts to the layout it finds.

Frequently Asked Questions

Upload the footage to OpenClip. Speaker diarization maps the questions and answers, the AI ranks exchanges by strength, face tracking frames the active speaker through a 9:16 crop, and word-level captions burn in. You review a ranked shortlist of complete exchanges instead of scrubbing raw footage — the first-pass edit that normally takes hours happens in minutes.

Usually a compressed version of both: the question provides the tension that makes the answer land, but a rambling question kills the hook. The strong pattern is a tight question (or its final sentence) followed by the full answer. Because OpenClip segments on exchange boundaries, you can trim the question side without breaking the clip's logic.

A static center crop of a two-shot shows the table between two half-faces — the classic failure. OpenClip tracks both faces and frames whoever is speaking, cutting between them as the exchange moves. For side-by-side remote layouts it frames the active tile. The result mimics a two-camera edit even from a single wide shot. More detail in the speaker tracking guide.

Specificity and surprise: a concrete number, a story with a turn, a claim that cuts against expectation, or visible emotion. Generic answers — even articulate ones — don't stop scrolls. OpenClip's ranking weights these signals, which is why its shortlist tends to match what a producer would pick from the transcript.

Yes — customer story sessions are structurally identical to media interviews, and the best 30-second testimonial is usually buried in a 40-minute call. The same detection surfaces it, and captions plus vertical framing make it feed-ready. See customer testimonial clips for that specific workflow.

If you have access to the recording or it's published on YouTube, yes — paste the link and clip your own strongest answers. Guests repurposing their appearances is one of the highest-leverage uses of this workflow, especially for LinkedIn distribution where a strong podcast answer becomes a week of posts.

The Best Answer in Your Interview Is Waiting to Be Found

Upload your interview to OpenClip and get the strongest exchanges back as speaker-tracked, captioned clips — the first-pass edit, done before your coffee cools.

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