A number of private and public insurers compensate workers whose hearing loss can be directly attributed to excessive exposure to noise in the workplace. The claim assessment process is typically lengthy and requires significant effort from human adjudicators who must interpret hand-recorded audiograms, often sent via fax or equivalent. In this work, we present a solution developed in partnership with the Workplace Safety Insurance Board of Ontario to streamline the adjudication process. In particular, we present the first audiogram digitization algorithm capable of automatically extracting the hearing thresholds from a scanned or faxed audiology report as a proof-of-concept. The algorithm extracts most thresholds within 5 dB accuracy, allowing to substantially lessen the time required to convert an audiogram into digital format in a semi-supervised fashion, and is a first step towards the automation of the adjudication process. The source code for the digitization algorithm and a desktop-based implementation of our NIHL annotation portal is publicly available on GitHub (https://github.com/GreenCUBIC/AudiogramDigitization).
翻译:一些私营和公共保险公司赔偿因过度接触工作场所噪音而直接造成听力损失的工人。索赔评估过程通常时间很长,需要人类裁定者作出重大努力,他们必须翻译往往通过传真或同等方式发送的手动录音带;在这项工作中,我们提出了与安大略省工作场所安全保险委员会合作开发的简化裁决过程的解决办法。特别是,我们提出了第一个声学数字化算法,能够自动从扫描或传真音学报告中提取听力阈值,作为概念的证明。算法在5 dB精确度范围内提取了大多数阈值,从而大大缩短了以半监督方式将音频表转换为数字格式所需的时间,这是实现裁决过程自动化的第一步。数字化算法和基于桌面执行我们的NIHL通知门户的源代码可在GitHub上公开(https://github.com/GreenCUBIC/AudicaDigitization)。