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Machine Learning Based Detection of Hearing Loss Using Auditory Perception Responses

机译:基于机器学习的听觉损失检测使用听觉感应响应

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Hearing loss or hearing impairment is the primary reason of deafness throughout the world. Hearing impairment can occur to one or both the ears. If hearing loss is identified in time, it can be minimized by practicing specific precautions. In this paper, we investigate the likelihood of detection of hearing loss through auditory system responses. Auditory perception and human age are highly interrelated. Likewise, detecting a significant gap within the real age and the estimated age, the hearing loss can easily be identified. Our proposed system for human age estimation has promising results with a Root Mean Square Error (RMSE) value of 4.1 years, and classification performance efficiency for hearing loss is 94%, showing the applicability of our approach for detection of hearing loss.
机译:听证会损失或听力障碍是世界各地耳聋的主要原因。听力障碍可能发生在一个或两个耳朵上。如果及时识别听力损失,则可以通过练习具体的预防措施来最小化。在本文中,我们通过听觉系统反应调查检测听力损失的可能性。听觉感知和人类年龄非常相互作为。同样地,检测在实阶段内的显着差距和估计的年龄,可以容易地识别听力损失。我们拟议的人类年龄估计系统具有有前途的结果,具有41岁的根均方误差(RMSE)值,听力损失的分类性能效率为94%,显示了我们检测听力损失的方法的适用性。

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