Auralis 🌌

Model Details πŸ› οΈ

Model Name: Auralis

Model Architecture: Based on Coqui XTTS-v2

License:

Language Support: English, Spanish, French, German, Italian, Portuguese, Polish, Turkish, Russian, Dutch, Czech, Arabic, Chinese (Simplified), Hungarian, Korean, Japanese, Hindi

Developed by: AstraMind.ai

GitHub: AstraMind AI

Primary Use Case: Text-to-Speech (TTS) generation for real-world applications, including books, dialogues, and multilingual tasks.


Model Description πŸš€

Auralis transforms text into natural, high-quality speech with exceptional speed and scalability. It is powered by Coqui XTTS-v2 and optimized for both consumer-grade and high-performance GPUs. Auralis is designed to meet real-world needs like long-text processing, voice cloning, and concurrent request handling.

Key Features:

  • Warp-Speed Processing: Generate speech for an entire novel (e.g., Harry Potter) in ~10 minutes.
  • Hardware Friendly: Requires <10GB VRAM on a single NVIDIA RTX 3090.
  • Scalable: Handles multiple requests simultaneously.
  • Streaming: Seamlessly processes long texts in a streaming format.
  • Custom Voices: Enables voice cloning from short reference audio.

Quick Start ⭐

from auralis import TTS, TTSRequest

# Initialize the model
tts = TTS().from_pretrained("AstraMindAI/xtts2-gpt")

# Create a TTS request
request = TTSRequest(
    text="Hello Earth! This is Auralis speaking.",
    speaker_files=["reference.wav"]
)

# Generate speech
output = tts.generate_speech(request)
output.save("output.wav")

Ebook Generation πŸ“š

Auralis converting ebooks into audio formats at lightning speed. For Python script, check out ebook_audio_generator.py.

def process_book(chapter_file: str, speaker_file: str):
    # Read chapter
    with open(chapter_file, 'r') as f:
        chapter = f.read()
    
    # You can pass the whole book, auralis will take care of splitting
    
    request = TTSRequest(
            text=chapter,
            speaker_files=[speaker_file],
            audio_config=AudioPreprocessingConfig(
                enhance_speech=True,
                normalize=True
            )
        )
        
    output = tts.generate_speech(request)
    
    output.play()
    output.save("chapter_output.wav")

# Example usage
process_book("chapter1.txt", "reference_voice.wav")

Intended Use 🌟

Auralis is designed for:

  • Content Creators: Generate audiobooks, podcasts, or voiceovers.
  • Developers: Integrate TTS into applications via a simple Python API.
  • Accessibility: Providing audio versions of digital content for people with visual or reading difficulties.
  • Multilingual Scenarios: Convert text to speech in multiple supported languages.

Performance πŸ“Š

Benchmarks on NVIDIA RTX 3090:

  • Short phrases (<100 characters): ~1 second
  • Medium texts (<1,000 characters): ~5-10 seconds
  • Full books (~100,000 characters): ~10 minutes

Memory Usage:

  • Base VRAM: ~4GB
  • Peak VRAM: ~10GB

Model Features πŸ›Έ

  1. Speed & Efficiency:

    • Smart batching for rapid processing of long texts.
    • Memory-optimized for consumer GPUs.
  2. Easy Integration:

    • Python API with support for synchronous and asynchronous workflows.
    • Streaming mode for continuous playback during generation.
  3. Audio Quality Enhancements:

    • Background noise reduction.
    • Voice clarity and volume normalization.
    • Customizable audio preprocessing.
  4. Multilingual Support:

    • Automatic language detection.
    • High-quality speech in 15+ languages.
  5. Customization:

    • Voice cloning using short reference clips.
    • Adjustable parameters for tone, pacing, and language.

Limitations & Ethical Considerations ⚠️

  • Voice Cloning Risks: Auralis supports voice cloning, which may raise ethical concerns about misuse. Use responsibly and ensure proper consent.
  • Accent Limitations: While robust for many languages, accents and intonations may vary based on the input.

Citation πŸ“œ

If you use Auralis in your research or projects, please cite:

@misc{auralis2024,
  author = {AstraMind AI},
  title = {Auralis: High-Performance Text-to-Speech Engine},
  year = {2024},
  url = {https://huggingface.co/AstraMindAI/auralis}
}
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