Deepgram’s Aura gives AI agents a voice

Deepgram has made a identify for itself as one of many go-to startups for voice recognition. Today, the well-funded firm introduced the launch of Aura, its new real-time text-to-speech API. Aura combines extremely real looking voice fashions with a low-latency API to permit builders to construct real-time, conversational AI agents. Backed by giant language fashions (LLMs), these agents can then stand in for customer support agents in name facilities and different customer-facing conditions.As Deepgram co-founder and CEO Scott Stephenson advised me, it is lengthy been attainable to get entry to nice voice fashions, however these had been costly and took a very long time to compute. Meanwhile, low latency fashions are likely to sound robotic. Deepgram’s Aura combines human-like voice fashions that render extraordinarily quick (sometimes in properly underneath half a second) and, as Stephenson famous repeatedly, does so at a low worth.Image Credits: Deepgram”Everybody now’s like: ‘hey, we’d like real-time voice AI bots that may understand what’s being stated and that may perceive and generate a response — after which they’ll communicate again,'” he stated. In his view, it takes a mixture of accuracy (which he described as desk stakes for a service like this), low latency and acceptable prices to make a product like this worthwhile for companies, particularly when mixed with the comparatively excessive price of accessing LLMs.Deepgram argues that Aura’s pricing presently beats nearly all its opponents at $0.015 per 1,000 characters. That’s not all that far off Google’s pricing for its WaveNet voices at 0.016 per 1,000 characters and Amazon’s Polly’s Neural voices on the similar $0.016 per 1,000 characters, however — granted — it’s cheaper. Amazon’s highest tier, although, is considerably dearer.”You must hit a actually good worth level throughout all [segments], however then you need to even have superb latencies, velocity — after which superb accuracy as properly. So it is a actually exhausting factor to hit,” Stephenson stated about Deepgram’s basic strategy to constructing its product. “But that is what we targeted on from the start and because of this we constructed for 4 years earlier than we launched something as a result of we had been constructing the underlying infrastructure to make that actual.”Story continuesAura presents round a dozen voice fashions at this level, all of which had been skilled by a dataset Deepgram created along with voice actors. The Aura mannequin, identical to the entire firm’s different fashions, had been skilled in-house. Here is what that seems like:https://techcrunch.com/wp-content/uploads/2024/03/deepgram_voice.mp3You can attempt a demo of Aura right here. I’ve been testing it for a bit and although you may generally come throughout some odd pronunciations, the velocity is actually what stands out, along with Deepgram’s present high-quality speech-to-text mannequin. To spotlight the velocity at which it generates responses, Deepgram notes the time it took the mannequin to begin talking (typically lower than 0.3 seconds) and the way lengthy it took the LLM to complete producing its response (which is usually just below a second).

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