docs/demo-video-script.md

SignBridge — Demo Video Script

Target length: 2:30 (≤ 3 min). Format: 1080p MP4, MP3 audio. Aspect ratio 16:9. Tools: QuickTime Player (Mac) for screen + camera capture, iMovie or CapCut for editing.

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Story arc (3 acts)

Time	Act	Beat
0:00–0:20	Hook	Open with the human problem; viewer must feel the gap.
0:20–1:30	Demo	Live SignBridge in action — both fingerspelling AND a motion sign.
1:30–2:30	Why AMD + close	Architecture diagram + concrete MI300X comparison + open-source ethics + URL.

Hard rule: no slide-by-slide voice-over reading. The demo should play live; voice-over should narrate what we're seeing, not summarise text on screen.

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Shot list

Act 1 — Hook (0:00 → 0:20)

Visual A (5 s): Plain background, bold text card fades in:

70 million deaf people. Interpreters cost $50–200 / hour. They're scarce.

Visual B (5 s): Text card → "What if your phone could just translate?"

Visual C (10 s): Camera shot of you (Lucas) in a quiet room, signing HELLO at the camera silently. No voice-over yet. Hold the silence — let the viewer feel that the sign means nothing to them.

Voice-over: (starts at 0:15)

"Most of us can't read this. SignBridge can."

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Act 2 — Live demo (0:20 → 1:30)

Setup (0:20 → 0:25): 5-second screen-recording of the live HF Space loading at huggingface.co/spaces/lablab-ai-amd-developer-hackathon/signbridge. URL bar visible. Tabs visible: "Snapshot" and "Record sign". This proves it's a live deployed product, not a slide deck.

Beat 2A — Fingerspelling (0:25 → 0:55):

Visual (split screen recommended): Left = your face/hand on webcam, right = the Gradio app receiving frames.

• Sign L clearly. Click the 📷 camera button in the preview. App shows "✓ added L (98%)".
• Sign U. Click 📷 again.
• Sign C. 📷.
• Sign A. 📷.
• Sign S. 📷.
• Click 🔊 Speak. App composes → speaks: "Lucas."

Voice-over during this beat:

"First, fingerspelling. I sign each letter, the app captures it, and—" (pause for the speak) — "composed in natural English."

Beat 2B — Motion sign (0:55 → 1:25):

Visual: Switch tabs to Record sign. Hit Record, sign HELLO (the wave-from-forehead motion), stop, click Submit.

• Detected: hello (85%). Click Speak.
• App says: "Hello."

Repeat one more sign for variety: THANK_YOU.

Voice-over:

"But fingerspelling alone isn't real ASL — most signs are motion. Hold-to-record captures the whole gesture, not just one frame. The system detects the motion across frames and..." (pause for the speak)

Beat 2C — Two-person scene (1:25 → 1:30): (optional but high-impact)

Visual: You sign something to a hearing person; they hear the AI say it; they react. Hold the human reaction for 2 seconds.

No voice-over during this beat — let the moment land.

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Act 3 — Architecture + AMD pitch (1:30 → 2:30)

Beat 3A — Architecture diagram (1:30 → 1:55):

Visual: Static slide showing the pipeline:

Webcam recording → ffmpeg → fine-tuned Qwen3-VL-8B (native video_url)
                                      ↓
                              Qwen3-8B (composer)
                                      ↓
                                gTTS (speech)
                  Both LLMs concurrent on a single AMD Instinct MI300X

Voice-over:

"Under the hood: our fine-tuned Qwen3-VL-8B receives the recorded clip natively via vLLM's video_url block, Qwen3-8B composes the sentence, gTTS speaks it — both Qwen models running concurrently on a single AMD Instinct MI300X. Vision and reasoning on one GPU."

Beat 3B — The MI300X comparison (1:55 → 2:15):

Visual: The comparison table from the walkthrough:

	MI300X 1×	H100 80 GB
V1 pipeline (~34 GB)	✅ comfortable	⚠ tight
V2 with Llama-3.1-70B FP8 (~70 GB extra)	✅ still fits	❌ doesn't fit

Voice-over:

"192 GB of HBM3. Same workload on NVIDIA H100 needs three GPUs. Practical accessibility tools running globally need the cost-and-availability profile that AMD enables."

Beat 3C — Substrate + close (2:15 → 2:30):

Visual: Final slide:

• "Open source, MIT — github.com/seekerPrice/signbridge"
• "Hugging Face Space — huggingface.co/spaces/lablab-ai-amd-developer-hackathon/signbridge"
• "ASL V1. Deaf-led teams own the rest."
• 🤟 SignBridge

Voice-over:

"SignBridge is open source under MIT. It's a substrate — Deaf-led organisations deploy it for their own languages. The hardest part of accessibility isn't building. It's deploying. AMD makes the deploying possible. Thanks for watching."

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Voice-over recording tips

• Record voice separately from screen capture (better audio quality). Use QuickTime "New Audio Recording" with a mic 6–12 inches away.
• One take, then cut. Don't try to dub multiple takes line-by-line.
• Cadence: ~140 words/min. Pause for 0.5 s after each section.
• If you have a good pop filter / lavalier, use it. AirPods Pro built-in mic is workable but compresses dynamics.

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Editing notes

• Captions/subtitles required. Burn in the spoken English text below the speaker's face throughout — both for accessibility and so judges can follow with sound off.
• Highlight the recognized token visually. When the app shows "detected: hello (85%)", zoom in or add a brief highlight box on that text — judges' eyes need to find it fast.
• Music: skip. The demo is loud enough on its own; background music distracts from the speech-output beats.
• Smooth transitions only — don't use fancy wipes; cut on action.
• Final cut export: 1080p, H.264, MP4, ≤100 MB if possible (lablab uploader has size limits).

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Prep before recording

• AMD Dev Cloud credit landed (so the live demo uses MI300X — this is the hackathon talk-track); fall back to HF Inference if not.
• Lighting: front-facing soft light. No back-window glare.
• Plain background (white wall ideal).
• Wear a contrasting solid colour (not patterns) — VLM accuracy improves.
• Webcam height: at eye level. Hands need to be in frame for signs.
• Test the live HF Space URL once before recording. If it errors, fix before pressing record.
• One dry run end-to-end with a stopwatch. Trim if over 2:45.

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Recording order (don't shoot in story order)

1. Live demo screen recording first — 3 takes of the full demo flow, pick the cleanest.
2. Voice-over second — record continuous narration over the picked demo take.
3. B-roll of you signing alone (Act 1 silent shot, Act 2C two-person reaction) — last, since they're easier to re-shoot.
4. Edit it together in iMovie / CapCut.
5. Export.
6. Upload to YouTube as Unlisted, copy URL.
7. Paste URL into lablab.ai submission form's "Video Presentation" field.

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Export checklist

• Length 2:00–3:00
• Captions visible throughout
• AMD Dev Cloud / MI300X mentioned by name ≥3 times
• Qwen3-VL mentioned by name ≥2 times (Qwen Special Reward eligibility)
• HF Space URL shown on screen at least once
• GitHub URL shown on screen at least once
• No copyrighted music / footage
• Speaker face visible (judges remember faces)
• Final shot: SignBridge logo + URLs