EmbeddingGemma 2: an open, lightweight multimodal embedding model
deepmind.google·6d ago
AI Engineering
Hacker News·Jul 26·5 min read
Inflect-Micro-v2: complete voice in 9.36M parameters
TL;DR
Inflect-Micro-v2 is a text-to-waveform speech synthesis model that achieves high-quality voice output with just 9.36 million parameters. It supports long text handling and can run on both CPU and CUDA environments.
✦ Why It Matters
Explore Inflect-Micro-v2 for your TTS needs and provide feedback to support its development.
Key Takeaways
- Utilize Inflect-Micro-v2 for efficient TTS applications.
- Experiment with deterministic seeds for consistent audio output.
- Deploy on CPU or CUDA for flexible performance.
- Test long text handling capabilities in your projects.
How It Works
Inflect-Micro-v2 employs a parameter-efficient architecture based on the VITS family, which integrates a phoneme frontend and a neural waveform decoder. This design allows it to generate high-quality speech from text while maintaining a compact size, making it suitable for local deployment.