Many cars now come with voice control, but you can’t really talk normally to such systems, and you often have to repeat a phrase to get the job done. That could change, however, with the introduction of voice interfaces that allow for a more natural back-and-forth between driver and dashboard.
Having a dialogue
“What we’re going to see in the very near future is the ability to have a dialogue,” says Charlie Ortiz, senior principal manager of the artificial intelligence and reasoning group at Nuance, a voice recognition technology company based in Massachusetts, USA. “You might say I want to listen to some Latin jazz, or suggest a particular musician.”
According to Ortiz, such technolomay appear within a few years. It will primarily allow for more natural control of dashboard features and retrieval of information such as directions.
“In the navigation domain, we’re developing methods to describe points of interest more abstractly,” he says. “I don’t always know the exact address of where I want to go. I want to be able to say ‘I want to go to a restaurant in the marina near the ballpark.’”
Thanks to new techniques and large quantities of training data, speech recognition has improved greatly, and Nuance supplies the technology to companies across numerous industries. It already provides voice control technology to carmakers including Ford, Hyundai and Chrysler.
Software that understands you
Nuance is now looking to build on that by offering greater understanding of speech. This is notoriously difficult though, because the meaning of words and sentences can vary dramatically depending on the context; so dialogue usually needs to be carefully constrained within certain areas. Conducting more complex conversations is a major goal for the lab at Nuance. Ortiz’s team is working to develop personal assistants capable of understanding more types of sentences and responding effectively when they do not comprehend.
And Ortiz believes that more fluent speech technology could be just around the corner, thanks to advances in parsing semantics. “The stars are aligning at just the right time,” he says. “There have been a lot of advances in various components — language-understanding and the reasoning back-end parts. One big challenge is to put these pieces together.”