Familiarity with voice interfaces through cloud-only voice assistants, like smart speakers, has put voice AI on the map with consumers and brands. The ubiquity of these solutions has transformed voice AI from a nice-to-have addition to a critical element of any company roadmap. Up until now, limited connectivity choices have kept the technology out of arm’s reach for a wide range of manufacturers of devices where an internet connection is either unnecessary, unavailable, or unwanted for their devices and customers.
While cloud-only voice assistants do have their benefits for a wide range of solutions, they can also result in higher manufacturing costs, subscription-based fees, and privacy concerns for device manufacturers. When big tech voice assistants, such as Google and Amazon, are in play, manufacturers face a lack of product differentiation and control, loss of customer relationships (and valuable data), and the threat of competition from the voice AI provider.
Edge and embedded voice assistants open the door to a world of possibilities for product solutions across industries. Whether the use case is for cars, cruise ships, QSRs, manufacturing, healthcare, vending machines, elevators, hearables, wearables, or another industry, embedded and edge voice assistants offer many benefits to users and OEMs.
Here are 5 benefits of embedded and edge voice assistants that make them ideal product solutions:
- Speed and accuracy
- Lower manufacturing costs
- Personalization with privacy
- Product functionality
- Product independence and differentiation
1. Speed and accuracy with voice assistants on the edge
Speed and accuracy are essential for all voice assistants, regardless of connectivity. In the past, embedded voice assistants were limited to simple command and control functions. If the user did not utter the right phrase, the voice interface simply didn’t work, or worse, proceeded to begin an operation not intended by the user. Limited capabilities and robotic sounding responses were key reasons manufacturers resisted adopting voice interfaces.
Today, advances in voice AI and chip technology have solved the challenges of legacy embedded voice AI by putting more Natural Language Understanding (NLU) directly onto the device. Now, embedded voice AI solutions with NLU technology on-device can accept queries using a range of phrases and respond naturally.