parler-tts-mini-expresso

Maintained By
parler-tts

Parler-TTS Mini: Expresso

PropertyValue
Parameter Count647M
LicenseApache 2.0
PaperResearch Paper
LanguageEnglish

What is parler-tts-mini-expresso?

Parler-TTS Mini: Expresso is a sophisticated text-to-speech model that represents a significant advancement in natural speech synthesis. This model is a fine-tuned version of Parler-TTS Mini v0.1, specifically optimized on the Expresso dataset to deliver enhanced control over emotions and consistent voice characteristics.

Implementation Details

The model utilizes a transformer-based architecture with 647M parameters, implementing state-of-the-art techniques for speech synthesis. It has been trained using a combination of three datasets: Expresso, Jenny, and LibriTTS-R, ensuring robust and versatile speech generation capabilities.

  • Supports multiple speaker identities: Jerry, Thomas, Elisabeth, and Talia
  • Implements emotion control including happy, confused, laughing, and sad tones
  • Offers high-quality audio generation with configurable speaking rates
  • Uses advanced prompt-based control for speech characteristics

Core Capabilities

  • Natural language-based control of speech generation
  • Consistent voice maintenance across different emotions
  • Support for emphasis and prosody control through punctuation
  • High-fidelity audio output with configurable quality levels
  • Efficient processing with both CPU and GPU support

Frequently Asked Questions

Q: What makes this model unique?

This model stands out for its ability to generate high-quality speech with precise control over emotions and speaker characteristics through natural language descriptions. Unlike many closed-source alternatives, it's fully open-source and provides comprehensive documentation for both usage and training.

Q: What are the recommended use cases?

The model is ideal for applications requiring expressive text-to-speech conversion, including audiobook creation, virtual assistants, and content localization. It's particularly useful when consistent voice character and emotional expression are important.

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