Feature extracting hearing aids for the profoundly deaf using a neural network implemented on a TMS320C51 digital signal processor

J. Walliker, J. Daley, A. Faulkner, I. Howard
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Abstract

Many people with profound hearing impairment, while able to detect amplified sound are often unable to make sense of what they hear. Conventional hearing aids which amplify, filter and compress the speech signal are of little use to them. It has been demonstrated that some profoundly deaf listeners are able to make better use of speech features such as voice fundamental frequency (Fx) and frication when they are presented in a simplified form matched to their residual hearing than when conventionally presented.
基于TMS320C51数字信号处理器的深度聋人特征提取助听器
许多有严重听力障碍的人,虽然能够察觉到放大的声音,但往往无法理解他们所听到的。传统的助听器对语音信号进行放大、过滤和压缩,对他们来说用处不大。研究表明,一些重度失聪的听者在以与其剩余听力相匹配的简化形式呈现时,能够更好地利用语音特征,如语音基频(Fx)和摩擦,而不是以常规方式呈现。
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