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首页> 外文期刊>Journal of Basic and Applied Physics >Sound Classification for Hearing Aids Using Time-frequency Images
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Sound Classification for Hearing Aids Using Time-frequency Images

机译：使用时频图像的助听器声音分类

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This paper presents a method for extracting features of real sound data from time-frequency images. The features are used for a sound classification equipped for hearing aids. As an application of hearing aids in mind, four classes of “classical music”, “speech”, “multi-talker noise”, and “speech in the noise” are prepared in order to classify the input signal of a hearing aid into useful classes. Although there are several possible ways to figure out which class the current input signal belongs to, an approach from image processing is utilized to find out appropriate features because 2D image (time-frequency image) can contain multifaceted information compared to 1D information (waveform or frequency response of sound), and can be regarded as comprehensive data. It is found that eight features are required to meet a certain quality of sound classification according to our investigation. Experimental results of the sound classification by some clustering machines using the proposed features have shown that accuracy of the classification was more than 95% with every clustering machine.
机译：本文提出了一种从时频图像中提取真实声音数据特征的方法。这些功能用于为助听器配备的声音分类。作为考虑到助听器的应用，准备了四类“古典音乐”，“语音”，“多讲话者噪声”和“语音中的语音”，以便将助听器的输入信号分类为有用的。类。尽管有几种可能的方法可以确定当前输入信号属于哪一类，但是由于2D图像（时频图像）与1D信息（波形或波形）相比可以包含多方面的信息，因此采用了图像处理方法来找出适当的特征。声音的频率响应），并且可以视为综合数据。根据我们的调查发现，要满足特定的声音分类质量，需要八个功能。通过使用所提出的特征对一些聚类机进行声音分类的实验结果表明，每台聚类机的分类准确率均超过95％。

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