AI Avatar & Talking Head Videos

Install the belt CLI skill: npx skills add belt-sh/​cli

AI Avatar & Talking Head Videos

Create AI avatars and talking head videos via inference.sh CLI.

Quick Start

Requires inference.sh CLI (belt). Install instructions

belt login

# Recommended: P-Video-Avatar (fastest, cheapest, built-in TTS)
belt app run pruna/​p-video-avatar --input '{
  "image": "https://portrait.jpg",
  "voice_script": "Hello, welcome to our product demo!",
  "voice": "Zephyr (Female)"
}'

Available Models

Start with P-Video-Avatar — it's 18x faster and 6x cheaper than alternatives, with built-in TTS, dynamic backgrounds, and 1080p support.

Cost & Speed Comparison

Examples

P-Video-Avatar (Recommended)

Generate avatar from portrait + text script with built-in TTS:

belt app run pruna/​p-video-avatar --input '{
  "image": "https://portrait.jpg",
  "voice_script": "Welcome to our product walkthrough. Today I will show you three key features.",
  "voice": "Puck (Male)",
  "voice_language": "English (US)",
  "resolution": "720p"
}'

With custom style control:

belt app run pruna/​p-video-avatar --input '{
  "image": "https://portrait.jpg",
  "voice_script": "This is exciting news!",
  "voice": "Aoede (Female)",
  "voice_prompt": "Enthusiastic and energetic tone",
  "video_prompt": "The person is presenting on stage with dramatic lighting",
  "resolution": "1080p"
}'

With audio file instead of TTS:

belt app run pruna/​p-video-avatar --input '{
  "image": "https://portrait.jpg",
  "audio": "https://speech.mp3"
}'

Full Workflow: Generate Portrait + Avatar

Use Pruna P-Image to generate the portrait, then create the avatar:

# 1. Generate a portrait image
belt app run pruna/​p-image --input '{
  "prompt": "professional headshot portrait of a young woman, neutral background, looking at camera, studio lighting, photorealistic",
  "aspect_ratio": "9:16"
}'

# 2. Create avatar video with built-in TTS
belt app run pruna/​p-video-avatar --input '{
  "image": "<image-url-from-step-1>",
  "voice_script": "Hi there! Let me walk you through our latest features.",
  "voice": "Zephyr (Female)"
}'

OmniHuman 1.5 (Multi-Character)

belt app run bytedance/​omnihuman-1-5 --input '{
  "image": "https://portrait.jpg",
  "audio": "https://speech.mp3"
}'

Supports specifying which character to drive in multi-person images.

Fabric 1.0 (Image Talks)

belt app run falai/​fabric-1-0 --input '{
  "image": "https://face.jpg",
  "audio": "https://audio.mp3"
}'

PixVerse Lipsync

belt app run falai/​pixverse-lipsync --input '{
  "video": "https://talking-head.mp4",
  "audio": "https://speech.mp3"
}'

Takes a video, not a still image. Omit audio and pass text (plus optional voice_id) to use the built-in TTS.

Full Workflow: TTS + Avatar (Non-TTS Models)

For models without built-in TTS (OmniHuman), generate speech first:

# 1. Generate speech — Inworld TTS-2 for expressive character voices
belt app run inworld/​text-to-speech-2 --input '{
  "text": "[friendly] Welcome to our product demo! [excited] Let me show you three features that will change how you work.",
  "voice_id": "Sarah",
  "delivery_mode": "CREATIVE"
}' > speech.json

# 2. Create avatar video with the speech
belt app run bytedance/​omnihuman-1-5 --input '{
  "image": "https://presenter-photo.jpg",
  "audio": "<audio-url-from-step-1>"
}'

Tip: For most use cases, P-Video-Avatar with built-in TTS is simpler — no separate audio step needed. Use this workflow only when you specifically need OmniHuman (multi-character) or PixVerse (realistic lipsync).

Full Workflow: Dub Video in Another Language

# 1. Transcribe original video
belt app run infsh/​fast-whisper-large-v3 --input '{"audio": "https://video.mp4"}' > transcript.json

# 2. Translate text (manually or with an LLM)

# 3. Generate speech in new language
belt app run falai/​kokoro-tts --input '{"prompt": "<translated-text>"}' > new_speech.json

# 4. Lipsync the original video with new audio
belt app run infsh/​latentsync-1-6 --input '{
  "video_path": "https://original-video.mp4",
  "audio_path": "<new-audio-url>"
}'

Avatar UGC Generation

Create UGC-style content with P-Video-Avatar — built-in TTS, no separate audio step needed:

# 1. Generate a relatable UGC-style portrait
belt app run pruna/​p-image --input '{
  "prompt": "casual selfie-style photo of a young woman in a cozy room, natural lighting, looking at camera, warm smile, authentic feel",
  "aspect_ratio": "9:16"
}'

# 2. Create UGC avatar video with built-in TTS
belt app run pruna/​p-video-avatar --input '{
  "image": "<image-url-from-step-1>",
  "voice_script": "Okay so I just tried this product and honestly? It is a game changer. I was not expecting to love it this much but here we are!",
  "voice": "Zephyr (Female)",
  "voice_prompt": "Excited, casual, authentic tone like talking to a friend",
  "video_prompt": "The person is talking casually to camera in their room, natural gestures",
  "resolution": "1080p"
}'

Why P-Video-Avatar for UGC

• All-in-one — built-in TTS means no separate audio generation step
• 30 voices, 10 languages — match your target audience
• Voice + video prompts — control tone, emotion, body language, and background independently
• 18x faster, 6x cheaper — produce UGC at scale vs. Fabric/​OmniHuman/​HeyGen
• 1080p support — platform-ready vertical video from a single portrait image

Batch UGC: Same Product, Multiple Presenters

# Generate 3 different presenters
for voice in "Zephyr (Female)" "Puck (Male)" "Aoede (Female)"; do
  belt app run pruna/​p-video-avatar --input "{
    \"image\": \"https://portrait.jpg\",
    \"voice_script\": \"This changed my morning routine completely. Five minutes and I am done.\",
    \"voice\": \"$voice\",
    \"voice_prompt\": \"Casual, authentic, like a real testimonial\",
    \"video_prompt\": \"Person talking to camera in a bright kitchen\",
    \"resolution\": \"1080p\"
  }"
done

Use Cases

• UGC & Marketing: Product demos, UGC-style ads with AI presenters
• Education: Course videos, explainers
• Localization: Dub content across 10 languages from one image
• Social Media: Consistent virtual influencer content
• Corporate: Training videos, announcements
• Gaming: Character avatars, NPC dialogue

Tips

• Use high-quality portrait photos (front-facing, good lighting)
• Audio should be clear with minimal background noise
• P-Video-Avatar supports built-in TTS — no need for a separate speech generation step
• P-Video-Avatar output aspect ratio matches the input image
• Generate portraits with pruna/​p-image using 9:16 aspect ratio for vertical videos
• OmniHuman 1.5 supports multiple people in one image
• LatentSync is best for syncing existing videos to new audio

Related Skills

# Dedicated P-Video-Avatar skill
npx skills add inference-sh/​skills@p-video-avatar

# Full platform skill (all apps)
npx skills add inference-sh/​skills@infsh-cli

# Text-to-speech (generate audio for non-TTS avatar models)
npx skills add inference-sh/​skills@text-to-speech

# Speech-to-text (transcribe for dubbing)
npx skills add inference-sh/​skills@speech-to-text

# Video generation
npx skills add inference-sh/​skills@ai-video-generation

# Image generation (create avatar images)
npx skills add inference-sh/​skills@ai-image-generation

Browse all video apps: belt app list --category video

Documentation

• Running Apps - How to run apps via CLI
• Content Pipeline Example - Building media workflows
• Streaming Results - Real-time progress updates