Hearing protection and communication in high noise environments using vibration sensing and neural network voice transformation

Abstract

In the United States alone, there are more than 9 million workers who are exposed to high levels of noise (> 85 dBA) that require hearing protection. Not only is there a risk of hearing damage due to these high noise levels, but it also prevents communication between people, leading to significant safety risks, including people not using hearing protection because of the desire to communicate. Workers in such high noise environments typically also wear safety glasses. This paper outlines an integrated system with safety glasses, hearing protection, and communication elements, using vibration sensing technology and a neural network based voice transformation routine. Data was collected to train the neural network based voice transformation. Recordings were made under various representative noise conditions, with some well exceeding sound pressure levels of 93 dBA, and Signal to Noise Ratios were extracted. In addition, experiments were conducted according to a modified ITU P.835 approach to determine intelligibility, naturalness and overall quality. The results demonstrate that with this approach, speech can be clearly understood in such high noise environments with this approach.