Voice AI Technology Is More Advanced Than You Might Think
Systems that can handle repetitive tasks have supported global economies for generations. But systems that can handle conversations and interactions? Those have felt impossible, due to the complexity of human speech. Any of us who regularly use Alexa or Siri can attest to the deficiencies of machine learning in handling human messages. The average person has yet to interact with the next generation of voice AI tools, but what this technology is capable of has the potential to change the world as we know it.
The following is a discussion of three innovative technologies are accelerating the pace of progress in this sector.
Experts in voice AI have prioritized technology that can alleviate menial tasks, freeing humans up to engage in high-impact, creative endeavors. Drive-through ordering was early identified by developers as an area in which conversational AI could make an impact, and one company appears to have cracked the code.
Creating a conversational AI system that can handle drive-through restaurant ordering may sound simple: load in the menu, use chat-based AI, and you’ve done it. The actual solutions aren’t quite so easy. In fact, creating a system that works in an outdoor environment—handling car noises, traffic, other speakers—and one that has sophisticated enough speech recognition to decipher multiple accents, genders, and ages, presents immense challenges.
The co-founders of Hi Auto, Roy Baharav and Eyal Shapira, both have a background in AI systems for audio: Baharav in complex AI systems at Google and Shapira in NLP and chat interfacing.
Baharav describes the difficulties of making a system like this work: “Speech handling in general, for humans, is hard. You talk to your phone and it understands you – that is a completely different problem from understanding speech in an outdoor environment. In a drive-through, people are using unique speech patterns. People are indecisive – they’re changing their minds a lot.”
That latter issue illustrates what they call multi-turn conversation, or the back-and-forth we humans do so effortlessly. After years of practice, model training, and refinement, Hi Auto has now installed their conversational AI systems in drive-throughs around the country, and are seeing a 90% level of accuracy.
Shapira forecasts, “Three years from now, we will probably see as many as 40,000 restaurant locations using conversational AI. It’s going to become a mainstream solution.”
“AI can address two of the critical problems in quick-serve restaurants,” comments Joe Jensen, a Vice President at Intel Corporation, “Order accuracy which goes straight to consumer satisfaction and then order accuracy also hits on staff costs in reducing that extra time staff spends.”
A second groundbreaking innovation in the world of conversational AI is using a technique that turns human language into an input.
The CEO of Whitehead AI, Diwank Tomer, illustrates the historical challenges faced by conversational AI: “It turns out that, when we’re talking or writing or conveying anything in human language, we depend on background information a lot. It’s not just general facts about the world but things like how I’m feeling or how well defined something is.
“These are obvious and transparent to us but very difficult for AI to do. That’s why jokes are so difficult for AI to understand. It’s typically something ridiculous or impossible, framed in a way that seems otherwise. For humans, it’s obvious. For AI, not so much. AI only interprets things literally.
