Study reveals potential breakthrough in hearing technology

RESEARCH

© Alexey Klementiev - Fotolia

Computer engineers and hearing scientists at The Ohio State University have made a potential breakthrough in solving a 50-year-old problem in hearing technology: how to help the hearingimpaired understand speech in the midst of background noise.

Researchers have used the latest developments in neural networks to boost test subjects’ recognition of spoken words from as low as 10 percent to as high as 90 percent with the hope that the technology will pave the way for next-generation digital hearing aids. Such hearing aids could even reside inside smartphones; the phones would do the computer processing, and broadcast the enhanced signal to ultra-small earpieces wirelessly. Several patents are pending on the technology, and the researchers are working with Starkey, as well as others around the world to develop the technology.

Conquering background noise has been a “holy grail” in hearing technology for half a century, explained Eric Healy, professor of speech and hearing science and director of Ohio State’s Speech Psychoacoustics Laboratory. “Focusing on what one person is saying and ignoring the rest is something that normal-hearing listeners are very good at, and hearing-impaired listeners are very bad at,” Healy said. “We’ve come up with a way to do the job for them, and make their limitations moot.” Key to the technology is a computer algorithm developed by DeLiang “Leon” Wang, professor of computer science and engineering, and his team. It quickly analyses speech and removes most of the background noise.

“For 50 years, researchers have tried to pull out the speech from the background noise. That hasn’t worked, so we decided to try a very different approach: classify the noisy speech and retain only the parts where speech dominates the noise,” Wang said.

The new algorithm was particularly affective against background babble, improving hearing-impaired people’s comprehension from 25 percent to close to 85 percent on average. Against stationary noise, the algorithm improved comprehension from an average of 35 percent to 85 percent. For comparison, the researchers repeated the test with people who were not hearing-impaired. They found that scores for the normal-hearing listeners without the aid of the algorithm’s processing were lower than those for the hearing-impaired listeners with processing. “That means that hearing-impaired people who had the benefit of this algorithm could hear better than students with no hearing loss,” Healy said. The researchers also believe that, as hearing aid electronics continue to shrink and smartphones become even more common, phones will have more than enough processing power to run the algorithm and transmit sounds instantly - and wirelessly - to the listener’s ears.

A new $1.8 million grant from the National Institutes of Health will support the research team’s refinement of the algorithm and testing on human volunteers.

Source: Journal of the Acoustical Society of America

Victoria Adshead, editor in chief of Audio infos UK