Researchers of computer engineering and hearing scientists at The Ohio State University have made a potential breakthrough in solving a 50-year-old problem: how to help the hearing-impaired understand speech in the midst of background noise.
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 hearing-impaired understand speech in the midst of background noise.
In the Journal of the Acoustical Society of America, they describe how they 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.
The researchers hope 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.
Key to the technology is a computer algorithm developed by DeLiang "Leon" Wang, professor of computer science and engineering, and his team. It quickly analyzes speech and removes most of the background noise.
They tested the algorithm's effectiveness against "stationary noise" a constant noise like the hum of an air conditioner and then with the babble of other voices in the background. The algorithm was particularly affective against background babble, improving hearing-impaired people's comprehension from 25 percent to close to 85 percent on average.
"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 technology is currently being commercialized and is available for license from Ohio State's Technology Commercialization and Knowledge Transfer Office.
The Ohio State University
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