首页> 外文期刊>The Journal of the Acoustical Society of America >Speech intelligibility prediction in hearing-impaired listeners based on a psychoacoustically motivated perception model
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Speech intelligibility prediction in hearing-impaired listeners based on a psychoacoustically motivated perception model

机译:基于心理听觉动机的听觉障碍者听觉语言清晰度预测

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摘要

Sensorineural hearing-impaired listeners suffer severely from deterioration in the processing and internal representation of acoustic signals. In order to understand this deterioration in detail, a numerical perception model was developed which is based on current functional models of the signal processing in the auditory system. To test this model, the individual's speech intelligibility in quiet and in noise was predicted. The primary input parameter of the model is the precisely measured audiogram of each listener. In a refined version of the model, additional input parameters are derived from predicting the individual's temporal forward masking and notched-noise measurements with the same model assumptions. The predictions of the perception model were compared with those of the articulation index (AI) and the speech transmission index (STI). The accuracy of prediction with the perception model is in the same range as with the AI and the STI. The model does not require a calibration function and has the advantage of a greater flexibility in including different processing deficits associated with hearing impairment. However, it requires more time for computation. For the hearing-impaired listeners examined so far the individually measured psychoacoustical parameters have only a secondary effect on the prediction as compared to the audiogram. Nevertheless, the underlying model is a first step toward a quantitative understanding of speech intelligibility and helps to distinguish between the influence of the ``attenuation'' and the ``distortion'' component of the hearing loss.
机译:感觉神经性听力受损的听众在听觉信号的处理和内部表示中会严重恶化。为了详细了解这种恶化,开发了一种数字感知模型,该模型基于听觉系统中信号处理的当前功能模型。为了测试该模型,预测了个人在安静和嘈杂状态下的语音清晰度。模型的主要输入参数是每个听众的精确测量的听力图。在模型的改进版本中,使用相同的模型假设,通过预测个人的时间前向掩蔽和缺口噪声测量值,可以得出其他输入参数。将感知模型的预测与清晰度指数(AI)和语音传输指数(STI)的预测进行了比较。感知模型的预测准确性与AI和STI处于同一范围内。该模型不需要校准功能,并且具有更大的灵活性,可以包括与听力障碍相关的不同处理缺陷。但是,这需要更多时间进行计算。到目前为止,对于听力受损的听众,与听力图相比,单独测量的心理声学参数对预测仅具有次要影响。尽管如此,基本模型是迈向定量理解语音清晰度的第一步,并有助于区分听力损失的“衰减”和“失真”成分的影响。

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