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首页> 外文会议>Proceedings of the 17th IASTED international conference on robotics applications ; Proceedings of the 11th IASTED international conference on biomedical engineering >ENHANCEMENT OF SHIMMER AND HNR IN OESOPHAGEAL SPEECH
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ENHANCEMENT OF SHIMMER AND HNR IN OESOPHAGEAL SPEECH

机译：食管语音中希默和HNR的增强

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This research work presents an oesophageal speech improvement algorithm using Wavelet and Kalman Filtering approach. In both techniques, it has been used different mother wavelet for wavelet approach and different measurement noises for Kalman filtering. People who have suffered from larynx cancer have enormously low intelligibility due to the surgery. A new algorithm has been developed to improve the speech quality. The algorithm consists of enhancing the Shimmer and HNR parameters using Discrete Wavelet Transform (DWT) and Kalman Filtering. By taking advantage of the Wavelet Transform's special time-frequency properties, a corrective algorithm in the form of a wave is applied for the signal intervals in which the shimmer measurement goes beyond normal levels. Therefore, an atomized control of the signal peaks is carried out, having an effect on the normalization of the shimmer. Regarding Kalman filtering, it is proved that the noise obtained from an oesophageal voice during periods of silence is the most suitable. The speech enhancement has been measured using Multidimensional Voice Program tool (MDVP).
机译：这项研究工作提出了一种使用小波和卡尔曼滤波方法的食道语音改善算法。在这两种技术中，已将不同的母子波用于小波方法，并将不同的测量噪声用于卡尔曼滤波。由于手术，患有喉癌的人的清晰度非常低。已经开发了一种新的算法来改善语音质量。该算法包括使用离散小波变换（DWT）和卡尔曼滤波来增强Shimmer和HNR参数。通过利用小波变换的特殊时频特性，将波形形式的校正算法应用于闪烁测量超出正常水平的信号间隔。因此，进行了信号峰值的雾化控制，从而影响了闪光的标准化。关于卡尔曼滤波，已证明在沉默期间从食道声音获得的噪声是最合适的。语音增强已使用多维语音程序工具（MDVP）进行了测量。

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