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Srushti Mund

srushti335

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reacted to hexgrad's post with 👍 about 1 month ago

I wrote an article about G2P: https://hf.co/blog/hexgrad/g2p G2P is an underrated piece of small TTS models, like offensive linemen who do a bunch of work and get no credit. Instead of relying on explicit G2P, larger speech models implicitly learn this task by eating many thousands of hours of audio data. They often use a 500M+ parameter LLM at the front to predict latent audio tokens over a learned codebook, then decode these tokens into audio. Kokoro instead relies on G2P preprocessing, is 82M parameters, and thus needs less audio to learn. Because of this, we can cherrypick high fidelity audio for training data, and deliver solid speech for those voices. In turn, this excellent audio quality & lack of background noise helps explain why Kokoro is very competitive in single-voice TTS Arenas.

reacted to fdaudens's post with 🔥 about 1 month ago

📢 SmolLM2 paper released! Learn how the 🤗 team built one of the best small language models: from data choices to training insights. Check out our findings and share your thoughts! 🤏💡 Check it out: https://huggingface.co/papers/2502.02737

reacted to retronic's post with 🔥 about 1 month ago

Colox, a reasoning AI model. I am currently working on a model smarter than GPT o1 that thinks before it speaks. It is coming tomorrow in the afternoon.

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