ELEVENLABS
Elevenlabs Voice Design V2 generates realistic, human-like speech directly from text with natural tone and emotion.
Avg Run Time: 13.000s
Model Slug: elevenlabs-voice-design-v2
Playground
Input
Output
Example Result
Preview and download your result.
API & SDK
Create a Prediction
Send a POST request to create a new prediction. This will return a prediction ID that you'll use to check the result. The request should include your model inputs and API key.
Get Prediction Result
Poll the prediction endpoint with the prediction ID until the result is ready. The API uses long-polling, so you'll need to repeatedly check until you receive a success status.
Readme
Overview
ElevenLabs Voice Design is an advanced AI-powered voice synthesis and transformation model developed by ElevenLabs, a company recognized for its cutting-edge work in ultra-realistic, context-aware speech generation. The model enables users to create, customize, and remix synthetic voices with high fidelity, offering granular control over vocal attributes such as gender, accent, style, pacing, and emotional tone. It is designed for professional creators, developers, and enterprises seeking versatile voice solutions for dubbing, narration, character design, and more.
The underlying technology leverages deep learning architectures trained on large, diverse datasets to capture subtle nuances in human speech. What sets ElevenLabs Voice Design apart is its ability to iteratively refine voices using natural language prompts, allowing users to achieve highly specific results tailored to their creative or business needs. The model supports features like voice remixing, style exaggeration, and pronunciation dictionaries, making it a unique tool for both artistic and practical applications.
Technical Specifications
- Architecture: Deep neural network (specific architecture details not publicly disclosed)
- Parameters: Not specified in public documentation
- Resolution: Supports professional audio output up to 48 kHz; standard quality at 128 kbps MP3 or WAV
- Input/Output formats: Accepts text prompts and reference audio; outputs MP3, WAV, and other standard audio formats
- Performance metrics: Latency varies based on computational settings; style exaggeration and speaker boost increase resource usage and latency
Key Considerations
- Adjust stability and similarity sliders to balance emotional range and fidelity to the original voice
- Lower stability for more expressive, dramatic performances; higher stability for consistent, monotone delivery
- High similarity settings may reproduce artifacts if the reference audio is low quality
- Style exaggeration enhances vocal style but increases computational load and may reduce stability
- Speaker boost subtly increases similarity but also raises latency
- Pronunciation dictionaries are essential for accurate rendering of names, acronyms, and specialized terms
- Experiment with prompt strength for subtle or dramatic voice transformations
- Volume and speed controls allow fine-tuning of output for different use cases
Tips & Tricks
- Use natural language prompts to specify desired voice attributes (e.g., "Create a male version of this voice with a British accent")
- Iteratively refine voices by adjusting prompt strength and model parameters until the desired result is achieved
- For lively performances, set stability lower and generate multiple samples
- For professional narration, keep stability high and similarity moderate
- Use pronunciation dictionaries to ensure correct pronunciation of unique words or phrases
- Avoid extreme values for speed and volume to maintain audio quality
- Style exaggeration should be used sparingly for special effects or character-driven projects
Capabilities
- Generates ultra-realistic synthetic voices with customizable attributes
- Supports voice remixing for gender, accent, style, and pacing changes
- Enables voice cloning and transformation from reference audio
- Produces high-quality audio suitable for professional applications
- Adapts to a wide range of creative and business needs
- Offers advanced control over emotional tone and vocal style
- Integrates pronunciation dictionaries for precise word rendering
What Can I Use It For?
- Professional dubbing and localization for film, TV, and games
- Audiobook narration with custom character voices
- Voiceovers for marketing, advertising, and explainer videos
- Character design for interactive media and storytelling
- Accessibility solutions such as personalized voice assistants
- Creative projects including podcasts, animations, and fan fiction
- Business applications like automated customer service and IVR systems
- Personal projects such as prank apps, celebrity voice emulation, and custom alerts
Things to Be Aware Of
- Style exaggeration and speaker boost increase computational requirements and latency
- Lower stability settings may result in unpredictable or overly dramatic outputs
- High similarity settings can reproduce unwanted artifacts from poor-quality reference audio
- Pronunciation dictionaries are only compatible with specific model versions
- Users report highly natural and expressive voice outputs, especially for character-driven projects
- Some users note occasional inconsistencies in emotional delivery across generations
- Resource requirements scale with advanced features; professional audio output demands more processing power
- Positive feedback centers on the model's realism, flexibility, and ease of use
- Negative feedback includes occasional latency and minor stability issues with extreme parameter settings
Limitations
- Requires high-quality reference audio for optimal cloning and transformation results
- Advanced features like style exaggeration may reduce stability and increase latency
- Not optimal for real-time applications with strict latency constraints
Pricing
Pricing Detail
This model runs at a cost of $0.20 per execution.
Pricing Type: Fixed
The cost remains the same regardless of which model you use or how long it runs. There are no variables affecting the price. It is a set, fixed amount per run, as the name suggests. This makes budgeting simple and predictable because you pay the same fee every time you execute the model.
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