Talking Head Production logo

Talking Head Production

Organization
inference-sh
talking-head-production

Talking head video production with AI avatars, lipsync, and voiceover. Recommended: P-Video-Avatar (fastest, cheapest, built-in TTS). Also covers OmniHuman, PixVerse, Fabric. Portrait requirements, audio quality, production workflows. Use for: spokesperson videos, course content, social media, presentations, demos. Triggers: talking head, avatar video, lipsync, lip sync, ai spokesperson, virtual presenter, ai presenter, omnihuman, talking avatar, video presenter, ai talking head, presenter video, ai face video, p-video-avatar

Overview

Publisherinference-sh
Repositoryskills
Skill nametalking-head-production
Stars
790
Forks
106
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by inference-sh on GitHub. Read the source before you install it.

Installation

Install the Talking Head Production AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/inference-sh/skills/tree/main/guides/video/talking-head-production
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/inference-sh/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/guides/video/talking-head-production .claude/skills/talking-head-production
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Talking Head Production in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Talking Head Production on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Talking Head Production is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

Talking Head Production

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

Quick Start

Requires inference.sh CLI (belt). Install instructions

bash
belt login

# Recommended: P-Video-Avatar (built-in TTS, fastest, cheapest)
belt app run pruna/p-video-avatar --input '{
  "image": "https://portrait.jpg",
  "voice_script": "Welcome to our product tour. Today I will show you three features that will save you hours every week.",
  "voice": "Zephyr (Female)"
}'

Portrait Requirements

The source portrait image is critical. Poor portraits = poor video output.

Must Have

RequirementWhySpec
Center-framedAvatar needs face in predictable positionFace centered in frame
Head and shouldersBody visible for natural gesturesCrop below chest
Eyes to cameraCreates connection with viewerDirect frontal gaze
Neutral expressionStarting point for animationSlight smile OK, not laughing/frowning
Clear faceModel needs to detect featuresNo sunglasses, heavy shadows, or obstructions
High resolutionDetail preservationMin 512x512 face region, ideally 1024x1024+

Generate a Portrait

bash
# Generate a professional portrait with P-Image
belt app run pruna/p-image --input '{
  "prompt": "professional headshot portrait of a friendly business person, soft studio lighting, clean grey background, head and shoulders, direct eye contact, neutral pleasant expression, photorealistic",
  "aspect_ratio": "9:16"
}'

Background Options

TypeWhen to Use
Solid colorProfessional, clean, easy to composite
Soft bokehNatural, lifestyle feel
Office/studioBusiness context
Dynamic (P-Video-Avatar)Use video_prompt to set background

Model Selection

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

ModelApp IDBuilt-in TTSBest For
P-Video-Avatarpruna/p-video-avatarYes (30 voices, 10 langs)Best overall: speed, cost, quality
OmniHuman 1.5bytedance/omnihuman-1-5NoMulti-character, gestures
OmniHuman 1.0bytedance/omnihuman-1-0NoSingle character
Fabric 1.0falai/fabric-1-0YesImage talks with lipsync
PixVerse Lipsyncfalai/pixverse-lipsyncYesLipsync an existing video

Cost & Speed Comparison

ModelSpeed (per sec of video)Cost per second
P-Video-Avatar~1.83s/s$0.025
OmniHuman 1.5~28s/s (15x slower)$0.16 (6.4x more)
Fabric 1.0~34s/s (18x slower)$0.14 (5.6x more)

Production Workflows

Simple: Text Script -> Video (P-Video-Avatar)

No separate TTS step needed — P-Video-Avatar has built-in voices:

bash
belt app run pruna/p-video-avatar --input '{
  "image": "https://portrait.jpg",
  "voice_script": "Hi there! I am excited to share something with you today.",
  "voice": "Puck (Male)",
  "voice_language": "English (US)",
  "resolution": "720p"
}'

With Style Control

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

Audio-Driven (Any Model)

Provide your own audio file:

bash
# P-Video-Avatar with custom audio
belt app run pruna/p-video-avatar --input '{
  "image": "https://portrait.jpg",
  "audio": "https://speech.mp3"
}'

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

Full Workflow: Generate Portrait + Avatar

bash
# 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)"
}'

With Separate TTS (for non-TTS models)

bash
# 1. Generate speech
belt app run falai/dia-tts --input '{
  "prompt": "[S1] Your narration script here."
}'

# 2. Create talking head
belt app run bytedance/omnihuman-1-5 --input '{
  "image": "https://portrait.jpg",
  "audio": "<audio-url-from-step-1>"
}'

Multi-Character Conversation

OmniHuman 1.5 supports up to 2 characters:

bash
# 1. Generate dialogue with two speakers
belt app run falai/dia-tts --input '{
  "prompt": "[S1] So tell me about the new feature. [S2] Sure! We built a dashboard that shows real-time analytics. [S1] That sounds great. How long did it take? [S2] About two weeks from concept to launch."
}'

# 2. Create video with two characters
belt app run bytedance/omnihuman-1-5 --input '{
  "image": "https://two-person-portrait.png",
  "audio": "<audio-url>"
}'

Long-Form (Stitched Clips)

For content longer than ~60 seconds, split into segments:

bash
# Generate clips with same portrait for consistency
belt app run pruna/p-video-avatar --input '{"image": "https://portrait.jpg", "voice_script": "Segment one..."}' --no-wait
belt app run pruna/p-video-avatar --input '{"image": "https://portrait.jpg", "voice_script": "Segment two..."}' --no-wait
belt app run pruna/p-video-avatar --input '{"image": "https://portrait.jpg", "voice_script": "Segment three..."}' --no-wait

# Merge all segments
belt app run infsh/media-merger --input '{
  "media_files": [
    {"file": "segment1.mp4"},
    {"file": "segment2.mp4"},
    {"file": "segment3.mp4"}
  ]
}'

Multilingual Content

P-Video-Avatar supports 10 languages with built-in TTS:

bash
# Spanish
belt app run pruna/p-video-avatar --input '{
  "image": "https://portrait.jpg",
  "voice_script": "Bienvenidos a nuestra demostración de producto.",
  "voice": "Kore (Female)",
  "voice_language": "Spanish"
}'

# Japanese
belt app run pruna/p-video-avatar --input '{
  "image": "https://portrait.jpg",
  "voice_script": "こんにちは、製品デモへようこそ。",
  "voice": "Leda (Female)",
  "voice_language": "Japanese"
}'

Dub Existing Video

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

# 2. Translate text (manually or with LLM)

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

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

Audio Quality (for non-TTS workflows)

When providing your own audio, quality directly impacts lipsync accuracy.

ParameterTargetWhy
Background noiseNone/minimalNoise confuses lipsync timing
VolumeConsistent throughoutPrevents sync drift
Sample rate44.1kHz or 48kHzStandard quality
FormatMP3 128kbps+ or WAVCompatible with all tools

Available Voices (P-Video-Avatar)

Female: Zephyr, Kore, Leda, Aoede, Callirrhoe, Autonoe, Despina, Erinome, Laomedeia, Achernar, Gacrux, Pulcherrima, Vindemiatrix, Sulafat

Male: Puck, Charon, Fenrir, Orus, Enceladus, Iapetus, Umbriel, Algenib, Algieba, Schedar, Achird, Zubenelgenubi, Sadachbia, Sadaltager, Alnilam, Rasalgethi

Languages: English (US), English (UK), Spanish, French, German, Italian, Portuguese (Brazil), Japanese, Korean, Hindi

Framing Guidelines

┌─────────────────────────────────┐
│          Headroom (minimal)     │
│  ┌───────────────────────────┐  │
│  │                           │  │
│  │     ● ─ ─ Eyes at 1/3 ─ ─│─ │ ← Eyes at top 1/3 line
│  │    /|\                    │  │
│  │     |   Head & shoulders  │  │
│  │    / \  visible           │  │
│  │                           │  │
│  └───────────────────────────┘  │
│       Crop below chest          │
└─────────────────────────────────┘

Common Mistakes

MistakeProblemFix
Low-res portraitBlurry face, poor lipsyncUse 1024x1024+ face region
Profile/side angleLipsync can't track mouth wellUse frontal or near-frontal
Noisy audioLipsync drifts, looks unnaturalUse built-in TTS or record clean
Too-long clipsQuality degradesSplit into segments, stitch
Sunglasses/obstructionFace features hiddenClear face required
Inconsistent lightingUncanny when animatedEven, soft lighting

Related Skills

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

# All avatar models
npx skills add inference-sh/skills@ai-avatar-video

# All video generation models
npx skills add inference-sh/skills@ai-video-generation

# Text-to-speech
npx skills add inference-sh/skills@text-to-speech

# Image generation (for portraits)
npx skills add inference-sh/skills@ai-image-generation

Browse all apps: belt app list

Frequently asked questions

What does the Talking Head Production AI skill do?

Talking head video production with AI avatars, lipsync, and voiceover. Recommended: P-Video-Avatar (fastest, cheapest, built-in TTS). Also covers OmniHuman, PixVerse, Fabric. Portrait requirements, audio quality, production workflows. Use for: spokesperson videos, course content, social media, presentations, demos. Triggers: talking head, avatar video, lipsync, lip sync, ai spokesperson, virtual presenter, ai presenter, omnihuman, talking avatar, video presenter, ai talking head, presenter video, ai face video, p-video-avatar

Why use Talking Head Production on TypingMind?

Because you install it once and use it with any model. Talking Head Production is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Talking Head Production in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/inference-sh/skills/tree/main/guides/video/talking-head-production. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Talking Head Production?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Talking Head Production?

As many as you like. As long as a model supports skills, you can use Talking Head Production with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Talking Head Production AI skill free?

It is published on GitHub by inference-sh. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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