Most approaches to creating AI presenter video require generating a full video character from scratch - which means the character looks like whatever the model decides they look like, not like anyone specific.
OmniHuman reverses this. You provide the person - as a single photo - and the audio. OmniHuman makes that specific person speak, sing, or present in sync with your audio, with natural body language that reflects what they are saying and how they are saying it.
The result is a video that looks like that person recorded it, not like an AI imagined what a person might look like while saying those words.
What OmniHuman Does
OmniHuman is ByteDance's human video animation model. It accepts a static image as the visual source and an audio file as the motion signal, and outputs a video in which the person in the image performs in sync with the audio.
The key technical distinction is how the motion is driven. Many earlier talking head models were purely phoneme-driven - they matched mouth shape to sound and that was it. OmniHuman was trained on 18,700 hours of human video footage, giving it a comprehensive understanding of how humans actually move when they speak, sing, or perform. The OmniHuman 1.5 update (August 2025) added a multimodal LLM layer that analyzes the semantic meaning and emotional content of the audio before generating motion - so a character speaking calmly and a character expressing excitement do not just have different mouth shapes, they have different body language, gesture patterns, and facial expression ranges.
Supported inputs:
- Portrait images (face + shoulders)
- Half-body images (face + upper body)
- Full-body images (complete person)
- Stylized illustrations and 2D cartoon characters
- Anthropomorphic animal characters
Audio inputs that work:
- Narration generated with ElevenLabs TTS
- Recorded speech (clean recording, minimal background noise)
- Music tracks (for singing applications)
- Dialogue audio
Output:
- Up to 30 seconds of video
- Aspect ratios: 16:9, 9:16, 1:1
- Lip-synchronized video with body movement and expression
Image Requirements and What Produces the Best Results
The image you provide is the visual foundation for everything the model generates. Investing in a good source image pays back in cleaner output.
What makes a good OmniHuman source image:
Clear, consistent lighting with no harsh shadows on the face. Front-facing or a slight angle - not in profile. Face fully visible with nothing occluding it (no hand over mouth, no hair falling across the eyes, no heavy accessories blocking the face). A neutral or natural expression as the starting point - the model will animate from here, so it does not need to be the expression you want in the video.
Background matters less than face clarity. A busy background does not prevent the model from animating correctly, but a very low-contrast background where the person blends in slightly can reduce the sharpness of body edge detection.
For AI-generated source images:
Generate with Flux 2 using a professional headshot prompt - clean studio lighting, plain or blurred background, front-facing, natural expression. The portrait guide at AI Portrait & Headshot Generator → covers the exact prompt structures that produce consistent portrait quality.
For illustrated or cartoon characters:
OmniHuman handles these well. The model applies naturalistic animation to stylized character designs. An illustrated character with a defined face, clear expression, and visible body can be animated with the same inputs as a photorealistic portrait. Good for YouTubers with illustrated personas, branded characters, or educational content with a defined character style.
Audio Inputs: How to Prepare Your Audio
The audio file drives everything - lip shape, body gesture, emotional register, movement timing. Audio quality and content both affect output quality.
For narration and presenter content:
Generate your script narration with ElevenLabs TTS on Cliprise. Select a voice style appropriate for your content - professional and confident for corporate content, warm and conversational for educational material. Keep the narration at a natural speaking pace. Very fast or very slow delivery affects the movement naturalness.
The most common mistake: running the audio through too much compression or adding music under the narration before using it as input. OmniHuman works best with clean, dry voice audio. If you want background music in the final video, add it in CapCut after generation - not mixed into the audio input.
For singing and musical performance:
Upload the music track directly. OmniHuman's gesture system interprets the musical qualities of the audio - tempo, energy, mood, dynamics - and generates performance movement that reflects them. The character's gestures align with the song's rhythm and energy, not just with the lyric phonetics.
For best singing results: use the highest quality version of the audio track available. Compressed MP3s at low bitrate produce less accurate sync than WAV or high-bitrate files. If your track is a demo or low-quality recording, the lip sync accuracy will reflect that.
For dialogue and multi-voice content:
OmniHuman animates one character per generation. For two-character dialogue, generate each character separately against their respective audio sections, then cut between them in CapCut. This produces a conversation-format video with two distinct characters and accurate lip sync for each.
What OmniHuman Produces Particularly Well
Singing and musical performance. This is OmniHuman's strongest use case relative to other avatar tools. The model interprets musical audio holistically - tempo, dynamics, emotional character - and generates movement that reflects it. Gestures build with the song's energy. Expression reflects the mood of the music. For an independent artist who wants performance footage without filming, this is the most natural output OmniHuman produces.
Full-body naturalistic gesture. Most talking head tools animate the face and maybe the shoulders. OmniHuman handles complete body animation - hand movements, weight shifts, body sway, co-speech gestures (the natural hand and arm movements humans make when speaking). For a full-body source image, you get a video of a complete person performing, not just a floating head.
Stylized and illustrated characters. The model is flexible about input aesthetics. A 2D cartoon character, an illustrated mascot, a stylized portrait with exaggerated features - OmniHuman applies naturalistic animation principles to whatever visual style the input presents. This makes it useful for branded character content, educational series with a defined character, and YouTube channels with illustrated personas.
Emotional range and semantic appropriateness. Because OmniHuman 1.5 analyzes the meaning and tone of audio before generating motion, characters performing emotional content - a speech, an expression of joy or grief, an enthusiastic product pitch - produce body language and expression that feels proportional to the content. Calm narration produces composed professional movement. Excited delivery produces more animated, energetic gestures.
Practical Production Workflows
Brand Spokesperson from a Portrait
Most businesses do not have the budget for a spokesperson to appear on camera for every FAQ answer, product update, and onboarding step. OmniHuman makes one portrait image + one voice style a recurring asset.
Workflow:
-
Generate a professional portrait with Flux 2 - or use a real photo if a specific person is the intended spokesperson. See AI Portrait & Headshot Generator → for prompts.
-
Generate the narration script with ElevenLabs TTS. Select a voice that matches brand tone. Keep each script under 30 seconds - this is OmniHuman's duration limit.
-
Animate with OmniHuman - upload portrait, upload audio. Output: the spokesperson delivering the script with natural movement and accurate lip sync.
-
In CapCut: add the spokesperson clip to timeline, optionally add a branded background, add lower-third text, add subtle background music at low volume under the narration. Export.
For recurring series (weekly product updates, FAQ videos, onboarding steps), this workflow produces consistent-looking output from the same source portrait every time. The spokesperson looks the same in every video because the input is the same source image.
YouTube Talking Head Without Recording
For creators who want to appear on camera without recording themselves - or who want an AI avatar version of themselves as a consistent YouTube presence:
- Take or generate a clean portrait image under good lighting.
- Record or generate your script narration.
- Generate with OmniHuman - outputs a talking head clip of the portrait delivering the narration.
- In CapCut: layer talking head clip over a relevant background (screen recording, product footage, slides). Add auto-captions.
The talking head clip does not need to be the only visual. It is common to cut between the talking head (for personal delivery) and supporting visuals (for demonstration) - the same edit structure as any talking head YouTube video.
See How to Create AI Talking Head Videos for YouTube →
Music Video Performance Footage
For an independent artist releasing a single who needs visual content:
- Select a portrait or full-body image of the artist (or AI-generated visual representation).
- Upload the music track.
- OmniHuman generates a performance clip in sync with the track - gestures matching the song's energy, expression reflecting the mood, lip sync following the vocals.
- Combine with atmospheric background clips from Seedance 2.0 or Kling 3.0.
- Edit together in CapCut for a complete music video.
For a 3-minute song: generate multiple 30-second OmniHuman performance clips from the same source image with the corresponding audio sections. Edit them into a continuous performance in CapCut, alternating with atmospheric B-roll.
See AI Music Video Production →
Multilingual Content from One Portrait
Generate the narration in multiple languages with ElevenLabs TTS (or with native-speaker recordings), then animate the same portrait with each language version. OmniHuman's lip sync adapts to the phoneme patterns of each language, so the speaker appears to be a native speaker of each version.
OmniHuman vs Kling AI Avatar API
Both models are on Cliprise and animate images with audio. They have different technical capabilities suited to different production needs.
| OmniHuman | Kling Avatar API | |
|---|---|---|
| Max video duration | 30 seconds | Up to 1 minute (narration) / 5 minutes (singing) |
| Frame rate | Standard | 48fps |
| Full-body animation | Strong | Upper body focus |
| Singing / music sync | Excellent | Good |
| Multilingual lip sync | English, Chinese | English, Japanese, Korean, Chinese |
| Stylized / cartoon input | Strong | Supported |
| Emotional expression | Semantics-driven (MLLM) | Expression-control (MLLM) |
| Output resolution | Up to 1080p | 1080p |
Choose OmniHuman when: Full-body animation is important, the content is music/singing, the source image is stylized or illustrated, or short clips (under 30 seconds) are the target.
Choose Kling Avatar when: Video needs to be longer than 30 seconds, you need higher frame rate (48fps), you are producing multilingual content in Japanese or Korean, or professional presenter format is the priority.
See Kling AI Avatar API Complete Guide →
Note
ByteDance OmniHuman is available on Cliprise alongside Kling Avatar, ElevenLabs TTS, and 45+ other models. Try Cliprise Free →
Related Articles
Avatar and talking head workflows:
- Kling AI Avatar API: Complete Guide →
- How to Create AI Talking Head Videos for YouTube →
- AI Avatar vs Real Person: When to Use Which →
- AI Spokesperson Video: Brand Presenters Without Actors →
- AI Avatar Generator 2026 →
Portrait image sources:
Audio for OmniHuman input:
- AI Voice Generator Guide →
- ElevenLabs on Cliprise: Complete Voice-Over Guide →
- Text to Speech AI 2026 →
Music workflows:
Models on Cliprise:
Published: March 19, 2026.
