Hyperframes Media

HyperFrames Media Preprocessing

Three CLI commands that produce assets for compositions: tts (speech), transcribe (timestamps), and remove-background (transparent video). Each downloads a model on first run and caches it under ~/.cache/hyperframes/. Drop the output into the project, then reference it from the composition HTML — see the hyperframes skill for the audio/video element conventions.

Text-to-Speech (tts)

Generate speech audio locally with Kokoro-82M. No API key.

npx hyperframes tts "Text here" --voice af_nova --output narration.wav
npx hyperframes tts script.txt --voice bf_emma --output narration.wav
npx hyperframes tts --list                       # all 54 voices

Voice Selection

Match voice to content. Default is af_heart.

| Content type | Voice | Why | | ----------------- | --------------------- | ----------------------------- | | Product demo | af_heart/af_nova | Warm, professional | | Tutorial / how-to | am_adam/bf_emma | Neutral, easy to follow | | Marketing / promo | af_sky/am_michael | Energetic or authoritative | | Documentation | bf_emma/bm_george | Clear British English, formal | | Casual / social | af_heart/af_sky | Approachable, natural |

Multilingual

Voice IDs encode language in the first letter: a=American English, b=British English, e=Spanish, f=French, h=Hindi, i=Italian, j=Japanese, p=Brazilian Portuguese, z=Mandarin. The CLI auto-detects the phonemizer locale from the prefix — no --lang needed when the voice matches the text.

npx hyperframes tts "La reunión empieza a las nueve" --voice ef_dora --output es.wav
npx hyperframes tts "今日はいい天気ですね" --voice jf_alpha --output ja.wav

Use --lang only to override auto-detection (stylized accents). Valid codes: en-us, en-gb, es, fr-fr, hi, it, pt-br, ja, zh. Non-English phonemization requires espeak-ng system-wide (brew install espeak-ng / apt-get install espeak-ng).

Speed

• 0.7-0.8 — tutorial, complex content, accessibility
• 1.0 — natural pace (default)
• 1.1-1.2 — intros, transitions, upbeat content
• 1.5+ — rarely appropriate; test carefully

Long Scripts

For more than a few paragraphs, write to a .txt file and pass the path. Inputs over ~5 minutes of speech may benefit from splitting into segments.

Requirements

Python 3.8+ with kokoro-onnx and soundfile (pip install kokoro-onnx soundfile). Model downloads on first use (~311 MB + ~27 MB voices, cached in ~/.cache/hyperframes/tts/).

Transcription (transcribe)

Produce a normalized transcript.json with word-level timestamps.

npx hyperframes transcribe audio.mp3
npx hyperframes transcribe video.mp4 --model small --language es
npx hyperframes transcribe subtitles.srt          # import existing
npx hyperframes transcribe subtitles.vtt
npx hyperframes transcribe openai-response.json

Language Rule (Non-Negotiable)

Never use .en models unless the user explicitly states the audio is English. .en models (small.en, medium.en) translate non-English audio into English instead of transcribing it. This silently destroys the original language.

1. Language known and non-English → --model small --language (no .en suffix)
2. Language known and English → --model small.en
3. Language unknown → --model small (no .en, no --language) — whisper auto-detects

Default model is small, not small.en.

Model Sizes

| Model | Size | Speed | When to use | | ---------- | ------ | -------- | ------------------------------------- | | tiny | 75 MB | Fastest | Quick previews, testing pipeline | | base | 142 MB | Fast | Short clips, clear audio | | small | 466 MB | Moderate | Default — most content | | medium | 1.5 GB | Slow | Important content, noisy audio, music | | large-v3 | 3.1 GB | Slowest | Production quality |

Music with vocals: start at medium minimum; produced tracks often need manual SRT/VTT import. For caption-quality checks (mandatory after every transcription), the cleaning JS, retry rules, and the OpenAI/Groq API import path, see [hyperframes/references/transcript-guide.md](../hyperframes/references/transcript-guide.md).

Output Shape

Compositions consume a flat array of word objects. The id field (w0, w1, ...) is added during normalization for stable references in caption overrides; it's optional for backwards compatibility.

[
  { "id": "w0", "text": "Hello", "start": 0.0, "end": 0.5 },
  { "id": "w1", "text": "world.", "start": 0.6, "end": 1.2 }
]

Background Removal (remove-background)

Remove the background from a video or image so the subject (typically a person — avatar, presenter, talking head) sits as a transparent overlay in a composition.

npx hyperframes remove-background subject.mp4 -o transparent.webm  # default: VP9 alpha WebM
npx hyperframes remove-background subject.mp4 -o transparent.mov   # ProRes 4444 (editing)
npx hyperframes remove-background portrait.jpg -o cutout.png       # single-image cutout
npx hyperframes remove-background subject.mp4 -o subject.webm \
  --background-output plate.webm                                   # both layers in one pass
npx hyperframes remove-background subject.mp4 -o transparent.webm --device cpu
npx hyperframes remove-background --info                           # detected providers

Uses u2net_human_seg (MIT). First run downloads ~168 MB of weights to ~/.cache/hyperframes/background-removal/models/.

Layer separation (--background-output)

Pass --background-output (or -b) to emit a second transparent video alongside the cutout: same source RGB, alpha is 255 − mask instead of mask. The cutout is the subject with a transparent background; the plate is the original surroundings with a transparent hole where the subject was.

| File | Alpha is… | Use it for | | -------------------------------- | --------------------------------------------------------- | --------------------------------------------------------------- | | -o subject.webm | The mask — subject opaque, background transparent | Foreground layer, place on top | | --background-output plate.webm | Inverse — surroundings opaque, subject region transparent | Bottom layer; put text or graphics between this and the subject |

Both outputs share the same --quality preset and run from a single inference pass — encode cost roughly doubles, segmentation cost stays the same. Only valid for video inputs and .webm/.mov outputs.

Hole-cut plate, not an inpainted clean plate. The subject region in plate.webm is fully transparent — composite something opaque under it to fill the hole. The single test for whether --background-output is the right tool: will anything ever be visible through the subject's silhouette where the subject used to be?

| Use case | Right tool | | ----------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------- | | Text/graphics between the cutout and the plate (this command's reason for existing) | Hole-cut (--background-output) | | Subject onto an unrelated scene | Just subject.webm; ignore the plate | | Show the room without the person, alone over no other content | Clean plate — needs an inpainter (LaMa, ProPainter, E2FGVI). Not this command. | | Replace the subject with a different subject | Clean plate — same as above |

If a user asks for "the room with the person removed" and intends to display it standalone, do not reach for --background-output. Tell them they need an inpainter.

Typical layered composition (the canonical hole-cut use case):

MAKE IT IN HYPERFRAMES

  

This is functionally equivalent to the text-behind-subject pattern below, but you don't need the original presenter.mp4 in the project — the plate replaces it. Useful when you want to ship just the two transparent layers and let the user drop arbitrary content between them.

Output Format

| Format | When | | --------------------- | ------------------------------------------------------------- | | .webm (VP9 + alpha) | Default. Compositions play this directly via `. | | .mov (ProRes 4444) | Editing in DaVinci/Premiere/FCP. Large files. | | .png` | Single-image cutout (still subject, layered over a backdrop). |

Chrome decodes VP9 alpha natively, so the .webm plugs into a composition like any other muted-autoplay video — see the hyperframes skill for the `` track conventions.

Quality presets

--quality fast|balanced|best controls only the VP9 encoder's CRF — segmentation quality is fixed.

| Preset | CRF | When | | ---------- | --- | ----------------------------------------------------- | | fast | 30 | Iterating, smaller file, looser color match | | balanced | 18 | Default. Visually identical for most uses | | best | 12 | Master / final delivery. Largest file, tightest match |

Compositing patterns — pick the right one

The cutout webm is a re-encoded copy of the source mp4's RGB. That choice has consequences depending on what you put behind it:

| Pattern | What's behind the cutout | Result | | -------------------------------------------------------- | ------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Cutout over a different scene (most common) | Static image, gradient, or unrelated video | Looks great. The cutout's RGB is the only source of the subject — no doubling, no edge halo. This is what remove-background is built for. | | Cutout over its own source mp4 (text-behind-subject) | Same mp4 the cutout was generated from | Two RGB sources for the same person. At default --quality balanced (crf 18) the doubling is barely visible; at --quality fast (crf 30) you'll see a faint color shift / edge halo. Use --quality best (crf 12) for masters. | | Cutout over a different take of the same person | Footage of the same subject | Will look like two separate people overlapping. Don't do this. |

Text-behind-subject (headline behind a presenter):

MAKE IT IN HYPERFRAMES

  

Two key rules:

1. **Wrap the cutout video in a non-timed `** and animate the wrapper's opacity, not the video element's. The framework forces opacity:1 on active clips (any element with data-start/data-duration), so animating the video's opacity directly is silently overridden. The wrapper has no data-*` attributes, so it's owned by your CSS/GSAP.
2. Both videos use data-start="0" and data-media-start="0" so the framework decodes them in sync from t=0. Late-mounting the cutout (data-start=3.3) introduces a seek + warm-up that lands a frame off the base mp4 — visible as one frame of misalignment at the cut.

Then GSAP-flip the wrapper opacity at the cut: tl.set(cutoutWrap, { opacity: 1 }, 3.3).

TTS → Transcribe → Captions

When there's no pre-recorded voiceover, generate one and transcribe it back to get word-level timestamps for captions:

npx hyperframes tts script.txt --voice af_heart --output narration.wav
npx hyperframes transcribe narration.wav   # → transcript.json

Whisper extracts precise word boundaries from the generated audio, so caption timing matches delivery without hand-tuning.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: boraoztunc
• Source: boraoztunc/skills
• License: Apache-2.0
• Homepage: https://bookmarker.cc

Install and usage instructions live in the source repository linked above.