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NOVEL ENDPOINT DETECTION ALGORITHM FOR SPEAKER RECOGNITION IN NOISY ENVIRONMENT

机译:嘈杂环境中说话人识别的新型端点检测算法

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Many papers have addressed speaker recognition, its importance and convenience in real applications, Finding an endpoint of speech is very important for speaker recognition. In a noise free environment, it is not difficult to do so by traditional methods, like short-time energy, zero-crossing rate, etc. However, if the speakers use the natural mode to give the utterance in real-life environment, the system's performance would degrade significantly because of additional noise and pause. This paper addresses a robust and efficient endpoint detection algorithm against noisy environment. In noisy condition where endpoint could not be determined precisely, one possible method is to shift reference model along test utterance (relax start-end point DTW [3]). We propose a method called 'three-step endpoint (3S-EP)' which results in nearly 20% ERR (Equal Error Rate) improvement over the baseline system.
机译:许多论文已经讨论了说话人识别,其在实际应用中的重要性和便利性。找到语音端点对于说话人识别非常重要。在无噪声的环境中,通过短时能量,过零率等传统方法并不难。但是,如果扬声器使用自然模式在现实环境中发出声音,则由于额外的噪音和暂停,系统的性能将大大降低。本文针对噪声环境提出了一种强大而有效的端点检测算法。在无法精确确定端点的嘈杂条件下,一种可能的方法是沿测试话语移动参考模型(松弛起始点DTW [3])。我们提出了一种称为“三步端点(3S-EP)”的方法,与基线系统相比,该方法可将ERR(相等错误率)提高近20%。

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