OuteTTS-0.3-1B
| Property | Value |
|---|---|
| Base Model | OLMo-1B |
| License | CC-BY-NC-SA-4.0 |
| Training Data | 20,000 hours of speech audio |
| Languages | English, Japanese, Korean, Chinese, French, German |
| Model URL | https://huggingface.co/OuteAI/OuteTTS-0.3-1B |
What is OuteTTS-0.3-1B?
OuteTTS-0.3-1B is an advanced text-to-speech synthesis model built on the OLMo-1B architecture. It's designed to extend existing large language models with TTS and speech-to-speech capabilities while maintaining compatibility with various libraries and tools. The model represents a significant advancement in natural speech synthesis, trained on an extensive dataset of 20,000 hours of speech audio, equivalent to approximately 8 billion tokens.
Implementation Details
The model introduces sophisticated punctuation support, converting marks like periods, commas, and question marks into special tokens for improved speech coherence. It's built with robust multi-language support and includes experimental voice control features, though these are still in early development.
- Comprehensive punctuation support including language-specific marks
- Integration with existing LLM architectures
- Optimized for 30-second generation batches
- Voice cloning capabilities through speaker profiles
Core Capabilities
- Multi-language support for 6 major languages
- Natural speech synthesis with punctuation awareness
- Speaker profile creation and management
- Flexible integration with existing LLM frameworks
- Support for various audio processing tasks
Frequently Asked Questions
Q: What makes this model unique?
The model's ability to handle multiple languages, extensive punctuation support, and integration capabilities with existing LLMs make it stand out. It's built on a substantial training dataset and offers voice cloning features while maintaining high compatibility with various tools.
Q: What are the recommended use cases?
The model is ideal for applications requiring natural speech synthesis in multiple languages, voice cloning applications, and integration with existing language models. It's particularly suitable for projects needing high-quality TTS with support for various speaking styles and languages.
