Hearing loss is rapidly becoming an area of interest and research. The number of baby boomers dealing with hearing loss continues to increase as they age. This interesting news came to us from Science Daily in their article, “Machine learning improves human speech recognition.”

Researchers are studying people’s ability to recognize speech to gain a better understanding of hearing loss and its impact. It is more difficult for people to recognize human speech if there is reverberation, some hearing impairment, or significant background noise, such as traffic noise or multiple speakers. They are exploring a human speech recognition model based on machine learning and deep neural networks.

In addition to predicting speech intelligibility, the model could also potentially be used to predict listening effort or speech quality as these topics are very related.

Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms. “Explainable AI” is used to describe an AI model, its expected impact and potential biases.

Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.