Finally, a novel robust feature parameter, Adaptive Subband Power Spectral Entropy (ASPSE), is presented to successfully detect endpoints in different background noises.

发现了一种新颖的鲁棒特征参数-自适应子带谱熵(aspse)，它能成功地在不同的背景噪声下检测语音端点。

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In order to use the robust feature in low computational resource device, on the basis of two-stage Wiener filtering algorithm in ETSI Standard, we propose a novel approach to improve the efficiency.

为了能够在低运算资源的设备上实现鲁棒性前端，在ETSI标准的核心两级维纳滤波算法的基础上，我们提出了一种新方法以提高算法效率。

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The experiment result proved that the multi-thread method solved the problem of accumulated-errors, and it is a robust feature based real-time registration method.

实验结果表明，该方法在实时的情况下，有效地解决了基于特征跟踪方法的误差累积问题，是一种准确、稳定、有效的自然特征注册方法。

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The experiment result proved that the multi-thread method solved the problem of accumulated-errors, and it is a robust feature based real-time registration method.

实验结果表明，该方法在实时的情况下，有效地解决了基于特征跟踪方法的误差累积问题，是一种准确、稳定、有效的自然特征注册方法。

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