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How Machine Learning Will Revolutionize Hearing Aids
A Machine Learning Primer)
Veröffentlicht am Jun 18, 2018
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When you hear the term “machine learning” what’s the first thing that comes to mind? Do you think of computers making us redundant in the workplace? Do you think of armed robot uprisings?
If your initial reaction to machine learning is negative, you aren’t alone. Most people know very little about what machine learning really is, or how the science of machine learning benefits us as individuals on a daily basis. While there are many academic definitions out there, machine learning is – in essence – the science of pattern recognition and pattern prediction by computers.
Let’s take a real-world example. In my personal Google Photos library, I can search for the term “cat” and Google returns pictures I’ve taken of my cat (Niko).
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How could Google possibly know about Niko? The answer, of course, is machine learning. Google has trained its software to recognize common objects and animals by exposing the software to millions of photos where the objects and animals have been identified. To get a better understanding of what Google “sees” in my images, I took the first photo of Niko and uploaded it to Google’s Vision API.
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… and amusingly, a little less certain that Niko was a mammal (we’re talking about machine learning here, not true human intelligence). Aside from that inconsistency, Google did a pretty good job of identifying the patterns in the image. To accomplish this feat, Google’s pattern recognition engine has been trained on millions of images of cats, mammals, whiskers, fur, etc. Note: We always thought Niko was a Tabby, but after looking at some pictures of “Dragon Li” breed cats, we’re reconsidering.
Aside from recognizing your cat photos, what are other real-world applications of machine learning that might impact your life?
How does the science of machine learning offer to improve hearing aids? Researchers in the field have offered a few concrete goals:
As any experienced hearing aid user knows, hearing in background noise is extremely difficult. Solving the background noise problem is the elusive holy grail of hearing aid technology, and while there have been a number of technological innovations since the dawn of digital hearing aids (like the directional microphone, and beamforming directionality), only incremental progress has been made in providing a solution.
Over the past few years, DeLiang Wang – a researcher out of Ohio State University – has been working on using machine learning and “deep neural networks” to help make it easier to hear a conversational partner in background noise. Wang’s software enables listeners (with normal hearing and hearing loss) to hear significantly better in background noise.
People in both groups showed a big improvement in their ability to comprehend sentences amid noise after the sentences were processed through our program. People with hearing impairment could decipher only 29 percent of words muddled by babble without the program, but they understood 84 percent after the processing.
Incorporating Wang’s software into a hearing aid would almost certainly revolutionize hearing aid technology, but unfortunately the software is not on the market yet. Based on the following statement, we can safely assume that there will be a significant wait before this technology will be available to consumers.
Eventually, we believe the program could be trained on powerful computers and embedded directly into a hearing aid, or paired with a smartphone via a wireless link, such as Bluetooth, to feed the processed signal in real time to an earpiece.
While the solution to background noise is still over the horizon, real progress has been made on improving sound quality and listening comfort through machine learning. The results of a recent double-blind study suggest that machine-learning can assist hearing aid users in more effectively finding their ideal sound settings; sound settings that lead to greater sound quality and listening comfort in a variety of difficult listening settings.
The good news? This technology has already hit the market, and is available globally right now. The technology is dubbed “SoundSense Learn”, and it’s available exclusively on the Widex EVOKE™ hearing aid platform. Here’s a description from Widex (we’ll try to break it down in simple terms below):
SoundSense Learn is an implementation of a well-researched machine learning approach for individual adjustment of hearing aid parameters. SoundSense Learn is designed to individualize hearing aid parameters in a qualified manner, sampling enough possible settings to adjust the hearing aid according to the users’ preference for his/her auditory intention with a high degree of certainty. From a practical perspective, this means the user is given control of a selected set of parameters using an application (app) that minimizes the number of interactions needed to reach an optimal setting.
