OuteTTS-0.1-350M

Maintained By
OuteAI

OuteTTS-0.1-350M

PropertyValue
Parameter Count362M parameters
Model TypeText-to-Speech
ArchitectureLLaMa-based
LicenseCC BY 4.0
LanguageEnglish

What is OuteTTS-0.1-350M?

OuteTTS-0.1-350M is an innovative text-to-speech synthesis model that revolutionizes the approach to voice generation by utilizing pure language modeling techniques. Built upon the LLaMa architecture and derived from the Oute3-350M-DEV base model, it demonstrates that high-quality speech synthesis can be achieved without complex external adapters or architectural modifications.

Implementation Details

The model employs a sophisticated three-step approach to audio processing: audio tokenization using WavTokenizer (processing 75 tokens per second), CTC forced alignment for precise word-to-audio token mapping, and structured prompt creation. The system utilizes a specific format: [full transcription] followed by [word] [duration token] [audio tokens].

  • Pure language modeling approach without external adapters
  • WavTokenizer integration for audio processing
  • CTC forced alignment technology
  • Structured prompt formatting system

Core Capabilities

  • Voice cloning functionality
  • Real-time text-to-speech conversion
  • Support for short to medium-length sentences
  • Compatible with llama.cpp and GGUF format
  • Adjustable temperature and repetition penalty settings

Frequently Asked Questions

Q: What makes this model unique?

This model stands out for its pure language modeling approach to text-to-speech synthesis, eliminating the need for complex external adapters while maintaining high-quality output. Its integration with the LLaMa architecture and ability to perform voice cloning makes it particularly versatile.

Q: What are the recommended use cases?

The model performs best with shorter sentences and is ideal for applications requiring basic text-to-speech conversion and voice cloning capabilities. It's particularly suitable for developers working with the llama.cpp ecosystem and those needing a lightweight TTS solution.

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