Same model, same audio: comparing 3 Audio-to-Face approaches in Unity

#unity3d #ai #devtools

We’ve been testing different Audio-to-Face approaches for real-time characters, and one thing became obvious very quickly:

Even with the same character and the same source audio, different systems can produce noticeably different facial animation.

So for this test, we compared three approaches under the closest conditions we could reproduce:

Mugen3D Audio To Face
NVIDIA Audio2Face
Convai

For this comparison, we mainly looked at three things:

Timing— how closely the mouth movement follows the speech
Mouth movement — how restrained or exaggerated the articulation feels
Overall naturalness — whether the face feels believable while speaking

What we observed

NVIDIA Audio2Face

NVIDIA provides a flexible and technically mature solution, especially for developers who want more control over the overall pipeline.

In our test, the facial movement felt relatively clear and structured, although bringing the workflow into Unity requires more integration work.

Convai

Convai produced noticeably larger mouth and facial movements in our test.

The result feels more expressive and performance-oriented, which can work well when combined with full-body character animation.

Mugen3D

Our current approach is more restrained.

We’re focusing on keeping the mouth movement closely aligned with the source audio without making every syllable feel overly exaggerated, while keeping the Unity integration lightweight.

A separate reference: Georgy Dev

We also looked at Georgy Dev’s Audio-to-Face result.

However, we did not have access to the same character setup, so we don’t think it would be fair to include it in the direct comparison above.

Visually, the result looked very polished in the material we reviewed, so we’re including it here only as an additional reference rather than treating it as an apples-to-apples benchmark.

That distinction is important to us: different character rigs, rendering setups and production pipelines can significantly affect how facial animation looks.