Once a fringe feature found only in luxury vehicles, voice recognition has moved into the mainstream as more automakers promise a seamless connection between your car, home and all the devices in between. The opportunity to reach consumers in their vehicles — and collect all that data — has automakers, tech giants like Amazon and Google, as well as investors scrambling for a share of the connected cars market.
But this is just the beginning. Voice recognition is expected to be an essential feature in future autonomous vehicles, which will see drivers ultimately surrendering the ability to control the car mechanically. Other applications for voice recognition are also emerging, including automated drones, two-wheelers and even air taxis.
The upshot? A market with significant growth potential and opportunities for investors and companies of all sizes.
The share of cars featuring in-car connected services, which voice recognition requires, grew to 45% in 2020 from 30% in 2018, and is expected to reach 60% by 2024, according to IHS Markit. Automakers keen to improve the consumer experience are driving that growth, said Kyle Davis, IHS Markit’s senior analyst for vehicle experience and connected car, noting that “one of the biggest aspects of the user experience is voice.”
Voice recognition is becoming more common, but that doesn’t mean the technology is always received well by consumers. J.D. Power surveys consistently show consumers complaining about voice recognition systems in vehicles, said John Scumniotales, director of products and design for Alexa Auto at Amazon. Scumniotales sees this as an opportunity to improve that experience with Alexa, and help Amazon gain an even larger foothold in the marketplace.
While there are clear giants in the voice recognition field, there won’t ever be one system or type of digital assistant in vehicles, according to Greg Basich, associate director of Strategy Analytics’ global automotive practice. “You’re going to see multiple systems,” Basich said. “So it’s definitely a growing space.”
Startups will have to contend with behemoths like Google and Amazon, Basich said, adding, “It’s a tough market if you’re a startup (…) You need to be doing something very new or very different.”
In his view, automakers prefer to work with larger, more established companies that can provide long-term support for the technology once it’s in the vehicle. Amazon’s Scumniotales agrees, as the big companies are at a huge advantage since it takes a significant amount of investment to build the technology and then to do it at the scale required for the automotive industry.
Yet, a closer look indicates there is not only room for a number of players, but automakers aren’t always placing their bets on the biggest companies.
Partnerships between automakers and Amazon Alexa or Google get much of the buzz. However, Cerence, a publicly traded company spun off from Nuance Communications in October 2019, actually controls 87% of the embedded virtual personal assistant market, according to Davis.
“The space is pretty small and we’re the largest and most entrenched player in it,” Cerence CTO Prateek Kathpal said in a recent interview. He believes that his company is small enough to take risks, innovate and not be hamstrung by funding issues like a traditional startup.
In January, the company unveiled Cerence Drive, its new platform for mobility assistants that integrates cloud and embedded technologies to provide what it describes as a more seamless and accurate AI voice-recognition experience. The system can support more than 70 languages and can understand commands when vehicle occupants are speaking multiple languages at the same time. It also can comprehend complex, multi-step queries and commands like, “Find directions to Starbucks and also call my mom.”
Cerence has landed a number of customers over the years, including BMW, which has been using the company’s technology since 2000. Simon Euringer, head of personal assistants and voice interaction at BMW, is particularly impressed by Cerence’s hybrid system, which operates both via an embedded system and in the cloud, and provides answers through whichever of the two systems is quicker at the time.