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This is the fastest text-to-speech and speech-to-text API out there. It's under 250 ms to first-byte latency. That's what we need to deploy conversational AI applications everywhere! (I can't wait for the death of automated voice machines.) Look at the attached video. For the first time, I could have...

185,560 次观看 • 2 年前 •via X (Twitter)

10 条评论

jordan rothstein ☎️ 的头像
jordan rothstein ☎️2 年前

1. Use Groq for even faster inference 2. Connect with Twilio 3. IVR is gone

Vaibhav 的头像
Vaibhav2 年前

Absolutely groundbreaking! Aura's sub-250 ms latency is a game-changer for conversational AI, bringing us closer to seamless, real-time dialogues with AI agents. Can't wait to dive into the demo and see this in action. The future of AI communication is here! #Deepgram #AIRevolution

Vaibhav 的头像
Vaibhav2 年前

Real-time voice agents need to be quick and natural. Aura's sub-250ms response times for dialogue sequences ensure conversations flow smoothly, without the awkward pauses of yesteryear's tech.

Vaibhav 的头像
Vaibhav2 年前

1/5 Deepgram's Aura is shaking up the text-to-speech scene, boasting the lowest latency for real-time voice AI. With human-like voices and lightning-fast responses, it's set to redefine conversational AI.

Osmosis 的头像
Osmosis2 年前

We can't recommend Deepgram enough. This team is awesome!

OP. Collins 的头像
OP. Collins2 年前

Check out Bland, just as good or even better

RameshR 的头像
RameshR2 年前

I will kill GUI

bog12345 的头像
bog123452 年前

Think of the application for translation of text and back to speech in a different language

synthian wall facer 的头像
synthian wall facer2 年前

banger

Vaibhav 的头像
Vaibhav2 年前

With Aura, Deepgram rounds out its Voice AI Platform, offering a one-stop-shop for devs to craft immersive voice AI experiences. From transcribing speech to generating lifelike voice responses, it's all here.

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Learn to build conversational AI voice agents in "Building AI Voice Agents for Production", created in collaboration with LiveKit and RealAvatar, and taught by dsa (Co-founder & CEO of LiveKit), Shayne (Developer Advocate, LiveKit), and Nedelina Teneva (Head of AI at RealAvatar, an AI Fund portfolio company). Voice agents combine speech and reasoning capabilities to enable real-time conversations. They're already being used to support customer service, to improve accessibility in healthcare, for entertainment applications, and for talk therapy. In this course, you’ll learn to build voice agents that listen, reason, and respond naturally. You’ll follow the architecture used to create the "AI Andrew" Avatar, a collaborative project between and RealAvatar that responds to users in what sounds like my voice. You’ll build a voice agent from scratch and deploy it to the cloud, enabling support for many simultaneous users. What you’ll learn: - Understand the fundamentals of voice agents, including key components like speech-to-text (STT), text-to-speech (TTS), and LLMs, and how latency is introduced at each layer. - Explore voice agent architectures and the trade-offs between modular pipelines and speech-to-speech APIs. - Explore how platforms like LiveKit mitigate latency issues with optimized networking infrastructure and low-latency communication protocols. - Learn how to connect client devices to voice agents using WebRTC—and why it outperforms HTTP and WebSocket for low-latency audio streaming. - Incorporate voice activity detection (VAD), end-of-turn detection, and context management to detect turns, handle interruptions, and manage conversational flow. - Understand the trade-offs between latency, quality, and cost in an example in which you build a voice agent and change its voice. - Equip your agent with metrics to measure latency at each stage of the voice pipeline and learn the key levers you can pull to make your agent faster and more responsive. The voice agents built in this course also incorporate voice technology from , a supporting contributor to the project. By the end of this course, you'll have learned the components of an AI voice agent pipeline, combined them into a system with low-latency communication, and deployed them on cloud infrastructure so it scales to many users. I’m looking forward to seeing what voice agents you build from this course! Please sign up here:

Andrew Ng

87,484 次观看 • 1 年前