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MakeItTalk

github.com

Free plan LinuxSelf-hosted
Visit github.com
Spec score 7.4 #20 of 28 in AI Video Lip Sync Tools

What it is

MakeItTalk is Linux, self-hosted software that creates expressive talking-head videos from one facial image and an audio track. Audio content drives lip movement and nearby facial motion, while speaker information influences expressions and other talking-head movement. The project describes use with human portraits, paintings, sketches, 2D cartoons, manga, and stylized caricatures, including faces or characters not seen during training. Its repository includes pretrained models, module training code, and Google Colab demos for natural faces. For human faces and paintings, the README calls for a centered 256×256 JPG portrait and a WAV file. Optional command-line settings adjust lip motion on the x and y axes and head-motion displacement. Local setup specifies Python 3.6, ffmpeg, and Python packages; cartoon face warping on Ubuntu also requires winehq-stable. Custom puppets are listed as a to-do item, and training sections for voice conversion, the speaker-aware branch, and image-to-image translation are marked unfinished. It is free open-source research code under CC BY-NC 4.0, allowing noncommercial use under that license.

Spec sheet

Purpose
MakeItTalk generates expressive talking-head videos from a single facial image, using audio as the only input.Read 4 Oct 2026 · github.com
License
The repository license is Creative Commons Attribution-NonCommercial 4.0 International, which permits licensed use for noncommercial purposes subject to its terms.Read 4 Oct 2026 · github.com
Available code
The repository includes pretrained models, training code for modules, and Google Colab demos for natural faces.Read 4 Oct 2026 · github.com
Custom puppets
The README lists creating custom puppets as a to-do item.Read 4 Oct 2026 · github.com
Image and audio input
For human faces and paintings, the README instructs users to provide a centered 256×256 JPG portrait and WAV audio file.Read 4 Oct 2026 · github.com
Local requirements
The README specifies Python 3.6, ffmpeg, and Python packages; cartoon face warping on Ubuntu also requires winehq-stable.Read 4 Oct 2026 · github.com
Motion controls
Optional command-line arguments adjust lip motion along the x and y axes and head-motion displacement.Read 4 Oct 2026 · github.com
Security and privacy
The repository page does not state security certifications or privacy practices.Read 4 Oct 2026 · github.com
Speaker-aware animation
The method separates audio content, which controls lip and nearby facial motion, from speaker information, which influences expressions and other talking-head dynamics.Read 4 Oct 2026 · github.com
Supported imagery
The project describes use with human portraits, paintings, sketches, 2D cartoons, manga, and stylized caricatures.Read 4 Oct 2026 · github.com
Training status
Voice conversion, speaker-aware branch, and image-to-image translation training sections are marked “Todo...”.Read 4 Oct 2026 · github.com
Unseen inputs
The method is described as generalizing to faces and characters not observed during training.Read 4 Oct 2026 · github.com

Plans and prices

Open-source research code Free CC BY-NC 4.0 · noncommercial use only Read 4 Oct 2026 · github.com

Every MakeItTalk plan and price →

Strong points and limits

Strong points

  • Supports portraits, paintings, cartoons, manga, and caricatures
  • Includes pretrained models and training code
  • Offers Google Colab demos for natural faces
  • Provides command-line motion controls
  • Free under CC BY-NC 4.0

Limits

  • Requires Python 3.6, ffmpeg, and packages
  • Ubuntu cartoon warping also requires winehq-stable
  • Custom puppets remain a to-do item
  • Several training sections are unfinished

Who it suits

It suits developers and researchers running Linux who want to generate talking-head videos from still images and audio. The described inputs also cover illustrated and stylized characters.

Verdict

MakeItTalk provides a focused, self-hosted way to animate varied still imagery with audio. Its setup requirements and unfinished areas matter for anyone planning local or custom training work.

Where Specifiction places it

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