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Machine Learning Based Detection of Hearing Loss Using Auditory Perception Responses

机译:基于听觉感知响应的基于机器学习的听力损失检测

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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:听力损失或听力障碍是全世界耳聋的主要原因。一只或两只耳朵可能会发生听力障碍。如果及时发现听力损失,可以通过采取特殊的预防措施将其减至最小。在本文中,我们调查了通过听觉系统反应检测到听力损失的可能性。听觉感知与人类年龄高度相关。同样,通过检测实际年龄和估计年龄之间的明显差距,可以轻松地识别出听力损失。我们提出的用于人类年龄估计的系统具有4.1年的均方根(RMSE)值,并且对听力损失的分类性能效率为94%,显示出令人鼓舞的结果,表明我们的方法可用于检测听力损失。

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