Minimax Voice Clone
Playground
MiniMax Voice Clone is a state-of-the-art voice synthesis model developed by MiniMax. It enables high-quality voice cloning from a short reference clip, producing speech that closely mimics the tone, accent, and personality of the original speaker.
Features
MiniMax Voice Clone
MiniMax Voice Clone is a state-of-the-art voice synthesis model developed by MiniMax. It enables high-quality voice cloning from a short reference clip, producing speech that closely mimics the tone, accent, and personality of the original speaker.
Key Features
-
High-Fidelity Voice Cloning
Generates speech that is perceptually close to the source speaker with natural prosody and pronunciation. -
Few-Second Voice Adaptation
Requires only a few seconds of reference audio to accurately replicate a voice. -
Emotion and Tone Control
Allows fine-tuned control over speaking style and emotion, useful for storytelling, games, and character dialogue. -
Multilingual Output
Supports voice cloning across different languages and smooth code-switching. -
Low-Latency Inference
Optimized for real-time use cases, including live interactions and dialogue generation.
Use Cases
- AI voiceovers for content creators and influencers
- Personalized digital assistants and chatbots
- Audiobook narration in a specific voice
- Interactive gaming and character voices
- Assistive speech for individuals with voice loss
Model Overview
MiniMax Voice Clone uses a neural TTS pipeline with robust speaker embedding and prosody modeling. It combines clarity, control, and speed, offering production-ready results in diverse environments.
Authentication
For authentication details, please refer to the Authentication Guide.
API Endpoints
Submit Task & Query Result
# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/minimax/voice-clone" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
"model": "speech-02-hd",
"need_noise_reduction": false,
"need_volume_normalization": false,
"accuracy": 0.7,
"text": "Hello! Welcome to Wavespeed! This is a preview of your cloned voice. I hope you enjoy it!"
}'
# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"
Parameters
Task Submission Parameters
Request Parameters
| Parameter | Type | Required | Default | Range | Description |
|---|---|---|---|---|---|
| audio | string | Yes | - | - | The uploaded file is cloned and supports formats such as MP3, M4A, and WAV. |
| custom_voice_id | string | Yes | - | - | Custom user-defined ID. Minimum 8 characters; must include letters and numbers and start with a letter (e.g., WaveSpeed001). Duplicate voice-ids will throw an error. |
| model | string | Yes | speech-02-hd | - | Specify the TTS model to be used for the preview. |
| need_noise_reduction | boolean | No | false | - | Enable noise reduction. Default is false (no noise reduction). |
| need_volume_normalization | boolean | No | false | - | Specify whether to enable volume normalization. If not provided, the default value is false. |
| accuracy | number | No | 0.7 | 0.00 ~ 1.00 | Uploading this parameter will set the text validation accuracy threshold, with a value range of [0,1]. If not provided, the default value for this parameter is 0.7. |
| text | string | No | Hello! Welcome to Wavespeed! This is a preview of your cloned voice. I hope you enjoy it! | - | The model will generate audio for the given text using the cloned voice and provide the result as a link for previewing the voice cloning effect. Limited to 2000 characters. |
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 | Array of URLs to the generated content (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.has_nsfw_contents | array | Array of boolean values indicating NSFW detection for each output |
| 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 Query Parameters
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 | Array of URLs to the generated content (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.has_nsfw_contents | array | Array of boolean values indicating NSFW detection for each output |
| 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 |