Combining the Renesas RZ/V Series vision AI microprocessor unit (MPU) and the low-power multimodal, multi-feature Syntiant NDP120 Neural Decision Processor , the solution enables low-power contactless operation for image processing in vision AI-based IoT and edge systems, such as self-checkout machines, security cameras, and video conference systems, and smart appliances such as robotic cleaning devices.
The joint solution features always-on functionality with quick voice-triggered activation from standby mode to perform object recognition, facial recognition, and other vision-based tasks that are critical functions in security cameras and other systems. For example, while user-defined voice cues drive activation and system operation, vision AI recognition tracks operator behavior and controls operation or issues a warning when suspicious actions are detected.
The multimodal architecture, say the companies, makes it easier to create contactless user experiences for vision AI-based systems. Using a dedicated, power-efficient chip for voice recognition reduces standby power consumption while speeding up system development because it is possible to develop software independently of the vision AI functionality.
“We anticipate that demand for multimodal systems that use multiple streams of input information – both image and voice – will increase moving forward as a way to improve both ease of use and safety,” says Hiroto Nitta, Senior Vice President and Head of SoC Business in the IoT and Infrastructure Business Unit at Renesas. “Through the collaboration between Renesas, a leader in low-power image AI technology, and Syntiant, a leader in voice AI technology, we will accelerate the adoption of low-power, ultra-small smart voice AI technology in embedded systems and deliver new combined solutions to customers globally.”
Syntiant CEO Kurt Busch says, "Voice-based user interfaces will make it possible for customers to deliver new user experiences that bring the next generation of innovative ideas from concept to reality. We’ve already shipped more than 15 million of our deep learning NDPs globally to enable always-on voice in a wide variety of consumer and industrial IoT