Parler-TTS Large v1
| Property | Value |
|---|---|
| Parameter Count | 2.33B |
| Training Data | 45K hours of audio |
| License | Apache 2.0 |
| Paper | Research Paper |
What is parler-tts-large-v1?
Parler-TTS Large v1 is a sophisticated text-to-speech model designed to generate high-quality, natural-sounding speech with controllable features. Built with 2.33B parameters and trained on 45,000 hours of audio data, it represents a significant advancement in speech synthesis technology.
Implementation Details
The model employs a transformer-based architecture and operates using F32 tensor types. It's implemented using the Hugging Face Transformers library and supports both random voice generation and specific speaker targeting through descriptive prompts.
- Supports conditional generation based on text descriptions
- Includes 34 predefined speaker profiles
- Generates audio at model-specific sampling rates
- Provides control over gender, background noise, speaking rate, pitch, and reverberation
Core Capabilities
- Natural language-guided speech generation
- Controllable voice characteristics through text prompts
- High-quality audio output with adjustable properties
- Support for both random and specific speaker voices
- Punctuation-based prosody control
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its ability to control speech characteristics through natural language descriptions and its open-source nature, allowing community development and modification. It's also notable for its large parameter count and extensive training data.
Q: What are the recommended use cases?
The model is ideal for applications requiring high-quality speech synthesis with specific voice characteristics, including audiobook creation, virtual assistants, and content localization. It's particularly useful when voice customization is needed through simple text descriptions.
