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Big KittyLitter update released - speech to text like codex's push-to-talk - light mode and a bunch of UI updates - choose mono or sans font - rate limits and context indicators - can oauth login remote codexes now too if they arent logged in - lots of other... show more

SIGKITTEN

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12,996 просмотров • 5 месяцев назад •via X (Twitter)

Anya Rossi• Live Now

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Vernon on Kpop 🐻‍❄️: I feel like Kpop sounds more and more like American pop instead of Kpop and i think a lot of people talk about that too so it makes me want to go back to like the 2000s or the early 2010s like when i was in elementary school like wonder girls, or big bang or 2NE1, all that. I think it’s because kpop producers always try to bring American sounds to kpop and make it their own thing and i think right now they got to the point where they’re too good. You can’t differentiate between Kpop and Pop, i mean you can but the gap has become more and more thin.

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Voicebox: Text-Guided Multilingual Universal Speech Generation at Scale blog: Large-scale generative models such as GPT and DALL-E have revolutionized natural language processing and computer vision research. These models not only generate high fidelity text or image outputs, but are also generalists which can solve tasks not explicitly taught. In contrast, speech generative models are still primitive in terms of scale and task generalization. In this paper, we present Voicebox, the most versatile text-guided generative model for speech at scale. Voicebox is a non-autoregressive flow-matching model trained to infill speech, given audio context and text, trained on over 50K hours of speech that are neither filtered nor enhanced. Similar to GPT, Voicebox can perform many different tasks through in-context learning, but is more flexible as it can also condition on future context. Voicebox can be used for mono or cross-lingual zero-shot text-to-speech synthesis, noise removal, content editing, style conversion, and diverse sample generation. In particular, Voicebox outperforms the state-of-the-art zero-shot TTS model VALL-E on both intelligibility (5.9% vs 1.9% word error rates) and audio similarity (0.580 vs 0.681) while being up to 20 times faster.

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.Balaji on public disclosed AI vs. public undisclosed AI: "Whenever I see a slide deck that has AI content in it, it just shows that either they're dumb or they think you're dumb." "They're dumb because they can't tell the difference between normal text and AI text, or they think you're dumb and they can get one over on you and spend a little bit of effort to just flood you with a bunch of words."

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