Nirman
AstraMindAI

AstraMindAI/xttsv2

Model Name: Auralis Model Architecture: Based on Coqui XTTS-v2 - license: Apache 2.0 - basemodel: XTTS-v2 Components Coqui AI License Langua...

Model Documentation

Auralis 🌌



Model Details 🛠️



Model Name: Auralis

Model Architecture: Based on Coqui XTTS-v2

License:
  • license: Apache 2.0
  • base_model: XTTS-v2 Components Coqui AI 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 🚀



    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 ⭐



    python
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 📚



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

    python
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 📊



    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 🛸



    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 📜



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

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

    Files & Weights

    FilenameSizeAction
    xtts-v2.safetensors 0.32 GB