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首页> 外文期刊>International journal of materials science >Efficient hybrid speech enhancement using PCA and ANFIS for hearing aids
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Efficient hybrid speech enhancement using PCA and ANFIS for hearing aids

机译：使用PCA和ANFIS作为助听器的高效混合语音增强

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摘要

More commonly, digital hearing aid user's make complaint regarding the complicatedness in understanding the speech in existence of background noise, which is still unresolved. In order to enhance the speech perception in a noisy atmosphere, several speech enhancement approaches have been formulated in digital hearing aids. But still there is no efficient technique to overcome this setback. In this research work, a speech enhancement algorithm is proposed for digital hearing aids. This scheme includes preprocessing, feature extraction and noise reduction block. The algorithms such as Principal Component Analysis (PCA) based Adaptive Neuro Fuzzy Inference System (ANFIS) is proposed in this research for enhancing the speech for digital hearing aids. A proposed speech enhancement algorithm is presented for the purpose of enhancing the speech intelligibility in noise for the near-end listener. Experimentation results of the proposed algorithm are compared with the existing spectral subtraction, wiener filter and genetic SVD based on SNR and PESQ, and it shows that the performance of the proposed algorithm is better than the existing approaches.
机译：更常见地，数字助听器用户抱怨在存在背景噪声的情况下理解语音的复杂性，这仍然没有解决。为了增强在嘈杂的气氛中的语音感知，已经在数字助听器中提出了几种语音增强方法。但是仍然没有有效的技术来克服这种挫折。在这项研究工作中，提出了一种用于数字助听器的语音增强算法。该方案包括预处理，特征提取和降噪块。在这项研究中，提出了基于主成分分析（PCA）的自适应神经模糊推理系统（ANFIS）之类的算法，以增强数字助听器的语音。为了提高近端听众在噪声中的语音清晰度，提出了一种语音增强算法。将该算法与基于SNR和PESQ的谱减法，维纳滤波器和遗传SVD进行了实验比较，结果表明该算法的性能优于现有方法。

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