PostHere is a new tts model, extremely lightweight. and one of if not the smallest neural tts models yet.

Here is a new tts model, extremely lightweight. and one of if not the smallest neural tts models yet. This new model, called sanoTTS by ampixa, is truly something to talk about simply because of its size. It clocks in at a remarkable 1.4MB, which is incredibly tiny for a neural text-to-speech system. This makes it a potential game-changer for applications where every megabyte counts, or where processing power is very limited. The model boasts fast inference and is multi-speaker, having been trained on the LibriTTS dataset. What's even more interesting is its ability to use speaker embeddings, meaning it can synthesize speech in the style of voices it hasn't directly encountered during training. That's quite a feat for such a compact model. Now, it's important to be realistic about its performance. While the size is groundbreaking, the audio quality isn't going to blow anyone away. The creators themselves openly state that the sound is "not good," though acceptable for specific uses. Expect speech that might sound a bit artificial or less natural compared to the high-fidelity voices we hear from larger, more resource-intensive models. This is the trade-off for its extreme leanness. So, where does sanoTTS shine? It's perfect for embedded systems, edge devices, or any low-resource environment where you need basic voice output and size or speed are priorities over pristine audio quality. Think of simple notifications, basic voice prompts on small devices, or quick prototyping where you just need to hear something spoken without much overhead. If you want to try it out, here are some simple steps using Python: pip install sanotts sanotts say "Hello" --voice heart -o hello.wav The main link to learn more and access the model is on Hugging Face: https://huggingface.co/ampixa/sanoTTS It is genuinely impressive to see how far researchers are pushing the boundaries of model compression. While sanoTTS won't replace your favorite high-quality voice assistant, it opens up new possibilities for AI on very constrained hardware. What are your thoughts on models that prioritize extreme lightness over audio fidelity? Have you encountered any situations where such a tiny TTS model would be incredibly useful? Remember to subscribe to t.me/iaosai for more updates on AI models and tools.