Sync React 1
Playground
Try it on WaveSpeedAI!Sync React-1 is a production-grade video-to-video lip-sync model. It maps any speech track to a target face, producing phoneme-accurate visemes and smooth timing while preserving identity, head pose, lighting, and background. Supports emotion and intensity control, multilingual speech, and long takes for talking-head content. Built for stable production use with a ready-to-use REST API, no cold starts, and predictable pricing.
Features
sync/react-1 is a production-ready audio-driven video animation model that syncs a subject in a video to an input audio track. It supports selectable emotion control and multiple animation modes (lips / face / head) to help you generate natural, expressive results for short clips with minimal setup.
Why it stands out
- Audio-to-video sync for fast talking-head and reaction style outputs.
- Emotion presets (happy / sad / angry / disgusted / surprised / neutral) to steer overall expression.
- Multiple control modes so you can animate only lips, or drive broader face/head motion.
- Simple workflow and predictable pricing for quick iteration.
Capabilities
-
Audio-driven lip sync for an input video
-
Emotion-conditioned expression steering
-
Mode control for different animation scopes:
-
lips: focus on mouth movement
-
face: include facial expression changes
-
head: include head motion cues (where supported by the model)
Parameters
| Parameter | Description |
|---|---|
| video* | Input video file or public URL. |
| audio* | Input audio file or public URL. |
| emotion | Expression preset: happy / sad / angry / disgusted / surprised / neutral. |
| model_mode | Animation scope: lips / face / head. |
Pricing
| Video Duration (s) | Total Price |
|---|---|
| 1 | $0.167 |
| 2 | $0.334 |
| 3 | $0.501 |
| 4 | $0.668 |
| 5 | $0.835 |
How to use
- Upload the video (best with a clear, front-facing subject).
- Upload the audio (speech, voiceover, or short dialogue).
- Choose emotion to steer expression tone.
- Choose model_mode (lips / face / head).
- Run the model and download the synced result.
Best Use Cases
- Short talking-head clips for creators and social media
- Dubbing and voiceover sync for character shots
- Expressive reaction clips with controlled emotion
- Rapid prototyping for dialogue-driven video concepts
Notes
- Best results: single subject, stable lighting, minimal motion blur, and a visible face.
- Use lips mode for the most conservative edits; use face/head when you want stronger performance and expression.
- Very long videos are billed at the 5-second cap, so trim to the segment you want to animate.
More Digital Human Models
-
wavespeed-ai/infinitetalk — Create realistic talking-head digital humans from a single portrait and audio, delivering stable lip sync and natural facial motion for voice-driven avatar videos.
-
wavespeed-ai/infinitetalk/multi — Multi-person talking avatar generation that syncs multiple faces to audio with consistent expressions and timing, ideal for dialogues, interviews, and group scenes.
-
kwaivgi/kling-v2-ai-avatar-pro — Pro-grade AI avatar video generation for high-fidelity digital humans with strong identity consistency and polished, production-ready results for marketing and creator content.
Authentication
For authentication details, please refer to the Authentication Guide.
API Endpoints
Submit Task & Query Result
set -euo pipefail
export WAVESPEED_API_KEY="your-api-key"
REQUEST_BODY=$(cat <<'JSON'
{
"video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
"audio": "https://interactive-examples.mdn.mozilla.net/media/cc0-audio/t-rex-roar.mp3",
"emotion": "neutral",
"model_mode": "face"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/sync/react-1" \
-H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
-H "Content-Type: application/json" \
-d "${REQUEST_BODY}")
TASK=$(printf '%s' "${SUBMIT_RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "${TASK}" | jq -r '.id // empty')
if [ -z "${PREDICTION_ID}" ]; then
printf 'Submission response did not contain a prediction id
' >&2
exit 1
fi
RESULT_URL=$(printf '%s' "${TASK}" | jq -r '.urls.get // empty')
if [ -z "${RESULT_URL}" ]; then RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"; fi
# 2. Poll until the prediction finishes.
while true; do
RESPONSE=$(curl --silent --show-error --fail-with-body \
"${RESULT_URL}" \
-H "Authorization: Bearer ${WAVESPEED_API_KEY}")
RESULT=$(printf '%s' "${RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')
case "${STATUS}" in
completed) printf '%s\n' "${RESULT}" | jq '.outputs'; break ;;
failed|cancelled|timeout) printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
created|processing) sleep 2 ;;
*) printf 'Unexpected status: %s
' "${STATUS}" >&2; exit 1 ;;
esac
doneParameters
Task Submission Parameters
Request Parameters
| Parameter | Type | Required | Default | Range | Description |
|---|---|---|---|---|---|
| video | string | Yes | - | Input video file (.mp4) | |
| audio | string | Yes | - | - | Input audio file (.wav) |
| emotion | string | No | neutral | happy, sad, angry, disgusted, surprised, neutral | Emotion prompt for the generation (single word emotions only) |
| model_mode | string | No | face | lips, face, head | Edit region for the model (lips/face/head). When head is selected, model generates natural talking head movements along with emotions + lipsync |
Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., “success”) |
| data.id | string | Unique identifier for the prediction, Task Id |
| data.model | string | Model ID used for the prediction |
| data.outputs | array | Output values, usually URL strings; some models return text strings or structured result objects (empty when status is not completed) |
| data.urls | object | Object containing related API endpoints |
| data.urls.get | string | URL to retrieve the prediction result |
| data.status | string | Status of the task: created, processing, completed, or failed |
| data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |
Result Request Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| id | string | Yes | - | Task ID |
Result Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., “success”) |
| data | object | The prediction data object containing all details |
| data.id | string | Unique identifier for the prediction |
| data.model | string | Model ID used for the prediction |
| data.outputs | array<string | object> | Array of generated outputs (empty when status is not completed). Items are usually URL strings, but may be text strings or structured result objects, depending on the model. |
| data.urls | object | Object containing related API endpoints |
| data.urls.get | string | URL to poll for the prediction result |
| data.status | string | Status: created, processing, completed, or failed |
| data.created_at | string | ISO timestamp of when the request was created |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |