Audio rises for event detection

July 26, 2016 // By Junko Yoshida
In advanced driver assistance systems (ADAS), CMOS image sensors — combined with vision processors — already play a critical role in helping a car recognize and classify what it sees. But what about what it hears? Will microphones ever play as important a role as cameras to add “intelligence” to autonomous cars? This is the plan.

Cars and drivers already hear its sirens well before they can spot an approaching ambulance, said Paul Beckmann, founder and CEO at DSP Concepts in a recent interview with EE Times. Why wouldn’t the automotive industry be interested in audio?

System OEMs — not limited to carmakers — are at the cusp of “using more microphones to generate yet another critical sensory data — audio — for artificial intelligence,” Beckmann explained.

As he envisions it, audio is “heading from pure playback” in entertainment systems to enabling “input, trigger and analytics in contextual awareness.”

The intelligence picked up by microphones can be used by every-day systems ranging from cars to digital virtual assistants and portable devices. “Sight and hearing go hand in hand,” added Willard Tu, DSP Concepts' executive vice president of sales and marketing. “Dogs barking, babies crying, glasses shuttering, cars honking, sirens wailing, gunshot noise…audio helps systems understand the environment [and the context] better.”



(Source: DSP Concepts) 

Two developments drive the electronics industry’s sudden exuberance for audio.

One is the proliferation of smartphones with multiple microphones per handset. Second is the popularity of digital virtual assistants like Amazon’s Echo and Google Home. Peter Cooney, principal analyst and director of SAR Insight & Consulting, observed “the increasing integration of virtual digital assistants into common consumer devices is driving awareness and adoption of voice as a natural user interface for many everyday tasks.”

But as to how soon microphones can go beyond offering a natural user interface, and start becoming a genuinely “intelligent sensor,” the industry still waits for a few advances.


To meet the challenge, audio needs microphones that can pick up better quality sound, processors good at post-processing audio, effective algorithms to pre-process audio, easier-to-use audio processing tools, an audio standard equivalent to Open GL used in graphics, and microphones that can remain always-on with minimal power drain.

In short, as Cooney noted, the market demands