Machine learning occurs when a learning algorithm is given data for teaching, and then asked to use those data to make decisions. More and more data are provided, which are then added to the teaching set and in turn improve accuracy. In essence, the machine is learning. This could be related to recognizing a photo or a person’s voice, learning how to talk with a human voice, or learning to drive a car.
It’s debatable whether a computer will ever “think” in the same way that the human brain does, but machines’ abilities to see, understand, and interact are changing our lives. It is no surprise then, that in the past few years we have seen mention of machine learning in hearing aid trade journal articles. But actually, machine learning in hearing aids isn’t new.
The first commercially available machine learning hearing aid was introduced 12 years ago in 2006 by Signia—the Model Centra.1 These hearing instruments had trainable gain. That is, the hearing aid would “learn” from the user’s VC (or remote control) adjustments what gain was preferred. Over time, our learning algorithm has continuously been improved to affect level-dependent gain in four frequency bands independently, and in different sound classes and programs.
In 2017, Signia introduced a new machine learning algorithm that only takes a few seconds. This unique learning algorithm was labeled Own Voice Processing (OVP™)—but importantly, it’s not just processing, it’s also voice recognition. Research with this new machine learning algorithm has clearly shown the benefits. Satisfaction with the sound of one’s own voice increases substantially, even when fitted with closed ear canal couplings.1 Likewise, hearing aid users report that the sound of their voice is significantly more natural when OVP is activated.2 And, perhaps most importantly, when OVP is used, new hearing aid users report that they are more engaged in conversations.3
To learn more about the how Signia has always been in the forefront of machine learning in hearing aids, click here.
1. Powers, T., Froehlich, M., Branda, E., & Weber, J. (2018). Clinical study shows significant benefit of own voice processing. Hearing Review. 25(2), 30-34.
2. Froehlich, M., Powers, T., Branda, E., & Weber, J. (2018, April). Perception of own voice wearing hearing aids: why “natural” is the new normal. AudiologyOnline, Article 22822. Retrieved from: http://www.audiologyonline.com
3. Powers, T. A., Davis, B., Apel, D., & Amlani, A. M. (2018). Own voice processing has people talking more. Hearing Review. 25(7), 42-45.