Orpheus TTS is a state-of-the-art open-source text-to-speech system leveraging a Llama-3b backbone to achieve human-sounding speech. It targets developers and researchers seeking natural intonation, zero-shot voice cloning, and controlled emotional expression, offering a significant advancement over existing closed-source solutions.

How It Works

Orpheus TTS utilizes a Llama-3b LLM for speech synthesis, demonstrating emergent capabilities in this domain. This approach allows for natural intonation, emotion, and rhythm. It supports zero-shot voice cloning without prior fine-tuning and enables control over speech characteristics via simple tags. The system is designed for low-latency streaming, achieving around 200ms, reducible to 100ms with input streaming.

Quick Start & Requirements

• Install via pip: pip install orpheus-speech (consider pip install vllm==0.7.3 if issues arise).
• Requires Python and a GPU for optimal performance.
• Official Colab notebooks are available for inference and fine-tuning.
• See official documentation for detailed setup and voice information.

Highlighted Details

• Achieves human-like speech with natural intonation, emotion, and rhythm.
• Supports zero-shot voice cloning without prior fine-tuning.
• Offers guided emotion and intonation control using tags like <laugh>, <sigh>.
• Provides ~200ms streaming latency, reducible to ~100ms.
• Includes multilingual models and data processing scripts for custom fine-tuning.

Maintenance & Community

The project is actively developed by Canopy AI. Feedback and questions are welcomed in the discussion forum.

Licensing & Compatibility

The README does not explicitly state the license. Compatibility for commercial use or closed-source linking is not specified.

Limitations & Caveats

The project is in a research preview stage, with ongoing work to fix glitches in real-time streaming and improve voice cloning implementation. Not all model sizes (1b, 400m, 150m) have been released yet.