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A novel approach based on Support Vector Machines for automatic speaker identification

机译:基于支持向量机的说话人自动识别新方法

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Over the past decade, the field of automatic speaker recognition has been the subject of extensive research looking for an efficient determination of a person's identity. Despite the essential role played by acoustic characteristics in order to discriminate between speakers. The research of discriminative information about a person remains a major challenge. The main objective of this paper is to present a new approach employing additional information which is dialect detection with a novel parameterization of the speech to improve the task of speaker identification. The superiority of the proposed system has been demonstrated by different kernels function of Support Vector Machines (SVM) with speakers taken from TIMIT database.
机译:在过去的十年中,自动说话人识别领域一直是寻求有效确定个人身份的广泛研究的主题。尽管声学特性起着至关重要的作用,以便区分扬声器。关于人的歧视性信息的研究仍然是一个重大挑战。本文的主要目的是提出一种利用附加信息的新方法,该方法是利用方言检测和语音的新型参数化来改善说话人识别的任务。支持向量机(SVM)的不同内核功能以及来自TIMIT数据库的扬声器都证明了该系统的优越性。

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