Speechify Simba 3.2 Tops Text-to-Speech Benchmarks

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OpenAI releases new voice models for more natural live conversations | TechCrunch What if you could just… talk? And the AI could talk back, naturally, handling interruptions and understanding your messy context? That future just got a lo Read more: https://lnkd.in/gF8xT-rj #AutoRunBiz #MalaysiaSME

"We've been asking the wrong question when it comes to voice AI." For years, the conversation has centred on one thing: Does it sound realistic? But that's only half the equation. A truly natural Voice AI conversation encompasses many different things. How quickly does it respond? Does it stay reliable under real-world conditions and at enterprise scale? In an interview with THE WEEK, our co-founder Sneha Roy shares why building great voice AI is about engineering the entire stack, from compute-efficient models and low-latency inference to consent-first AI and enterprise-grade governance. Read here: https://lnkd.in/gxwsaYg3 #VoiceAI #MurfFalcon

Well, this paper actually just proved our point LLMs are way better at handling UI as visuals rather than text Manipulating no-code platforms using AI agents is miles cheaper and more reliable in the long run https://lnkd.in/d2HzMcA9

How we built a realtime system for responsive voice AI in six months | hints from OpenAI on voice conversational AI agents https://lnkd.in/geSKjuDk

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You probably seen the announcement, but it is something that you really need to pay attention to if you work in CX or use AI voice in any product. The continuous model OpenAI launched today with GPT-Live is what your customer would want once they try it. No more turn based, no more cascading, this is where the bar is right now. I will add it to my evaluation harness once it is usable via API, but for now: go try it and speak to the future. https://lnkd.in/gYEFn3YR

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I spent last night comparing two voice assistants and confirming that the thing I’ve been reacting to for months was never the voice itself. Most voice AI gives you a simplified conversational layer sitting in front of the real model. You’re not talking to the intelligence, you’re talking to a lightweight proxy built for speed. It sounds natural, it answers fast, and it stops. Claude’s new voice mode and GPT’s Standard voice do something different. They put the actual model on the line. Speech in, speech out, and the thinking behind the speech is the same thinking you’d get in text. When I ask it to sit with an idea for fifteen minutes while one memory surfaces and connects to another, it can stay with me. What convinced me this is about architecture and not audio was a small test. Last week I asked GPT’s Live voice to go more in depth on a topic we were discussing. Not a vague hope, a direct instruction. It gave me slightly more and then clipped. The intelligence was clearly behind the curtain, but something in the interface capped how much of it reached me before it spoke. That isn’t a less capable model. It’s a cap, and it’s being sold as a feature. The pitch for fast voice is that people want quick answers. Some do, some of the time. But I don’t need a separate mode for that. I can tell any capable assistant “I’m driving, give me the short version” and it will. The instruction lives with me, turn by turn. What I object to is an interface that makes the depth decision for me up front and then can’t hear me ask for it back. I’ve said the same thing about rolling AI into companies. Don’t take judgment away from the human unless there’s a compelling reason. A voice mode that defaults every conversation to speed has quietly taken a judgment call away from me and dressed it as convenience. The direction is encouraging. Anthropic has now shipped voice that preserves the intelligence of the underlying model instead of flattening it into quick exchanges. That’s the bar worth holding all the labs to.