Deepgram Launches Aura, a Text-to-Speech API for Real-Time, Conversational Voice AI Agents
Deepgram Launches Aura, a Text-to-Speech API for Real-Time, Conversational Voice AI Agents
With Aura, developers can now build production-grade, secure, and human-like voice AI applications that run faster and more efficiently than any other solution on the market
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Deepgram, the leading provider of speech recognition, natural language processing, and generative AI solutions, today announced the public release of Aura, a text-to-speech (TTS) API that delivers human-like quality conversation that is faster and more efficient compute-wise than all voice AI alternatives. Aura is designed for developers who want to build real-time, conversational voice AI agents that can interact with customers, employees, and other users in a natural and engaging way.
This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20240312857580/en/
Aura is Deepgram's new AI Text-to-Speech (TTS) solution for enterprises and developers that compliments their industry-leading Speech to Text Platform, Nova-2 (Graphic: Business Wire)
Deepgram believes that voice will become the predominant way we interact with technology – and for that to work, AI systems must be highly tuned to enable natural conversation at scale and with incredibly low latency. Aura can generate speech from any text input, including responses from LLMs like ChatGPT, in fractions of a second. This enables fluid and natural-sounding conversations with AI agents that can handle complex and dynamic scenarios. Aura offers a selection of diverse voices strongly suited for conversational use cases and preferences requiring the highest degrees of safety, security, speed, and scale.
Aura perfectly complements Deepgram's Nova-2 speech-to-text API, which provides industry-leading accuracy and transcription speed of audio streams and is implemented at global enterprises and organizations including Spotify, Citibank, NASA, and Twilio. With this release, Deepgram offers developers a complete voice AI platform, giving them the essential building blocks they need – from transcription to sentiment analysis to voice synthesis – to build high throughput, real-time AI agents of the future.
"We are thrilled to launch Aura, our text-to-speech API, to the public after seeing the overwhelming demand for our early access product in the fall. Aura is the result of years of research and development by our team of world-class AI scientists and engineers, who have leveraged the latest advances in deep learning and GPU technology to create a state-of-the-art TTS solution that outperforms anything else on the market," said Scott Stephenson, CEO and co-founder of Deepgram. "With Aura, we are empowering developers to create voice AI applications that can truly understand and respond to human speech, opening up new possibilities for enhancing customer experience, productivity, and innovation."
Developers can sign up for a free account and start using Aura today by visiting https://deepgram.com/product/text-to-speech. Deepgram offers flexible pricing plans for different needs and budgets including a generous pool of free credits for new users to get started.
About Deepgram
Deepgram is the leading voice AI platform provider for enterprises and conversational AI leaders. Deepgram's end-to-end deep learning platform delivers accurate, fast, and scalable speech recognition, voice synthesis, and spoken language understanding for voice-enabled applications, such as call analytics, virtual assistants, customer service agents, and transcription services. Deepgram is on a mission to unlock the value of voice data and make voice AI accessible and affordable for everyone. Founded in 2015, Deepgram is backed by Madrona, Nvidia, Y-Combinator, Wing VC, and other investors. For more information, visit https://deepgram.com or follow us on Twitter @deepgram.
Josh Fox for Deepgram, josh.fox@deepgram.com
View source version on businesswire.com: https://www.businesswire.com/news/home/20240312857580/en/
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