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Biometric System Based on Voice Recognition Using Multiclassifiers

机译:基于MultiClassifiers的语音识别的生物识别系统

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In this paper we present a new speaker recognition system based on the fusion of two identification classifiers followed by a verification step. The user pronounces two passwords: the first one is composed by three words uniquely combined from a set of 21 possible words, while the second password represents the name of the user. The first step of the proposed system uses the first password to feed two identification classifiers: a speaker identification system (text independent) and a isolated word identification system (speaker independent). The isolated word identification system is constructed as the fusion of three classifiers, one for each word of the first password. The aim of this first step is to identify a couple speaker/password corresponding to the first password by combining the results of the two identification classifiers. A verification system is then applied on the second password in order to confirm or infirm the identification result (speaker identity) given by the fusion above. Compared with a state of the art speaker recognition system (text dependent) that gives an EER of 4.76%, the first step of the proposed system provides an EER of 0.38%, while the second step an EER of 0.26% for a text independent verification and of 0.13% for a text dependent verification.
机译:在本文中,我们提出了一种基于两个识别分类器的融合的新扬声器识别系统,然后是验证步骤。用户发出两个密码:第一个单词由三个单词唯一组合从一组21个可能的单词组成,而第二个密码表示用户的名称。所提出的系统的第一步使用第一个密码来馈送两个识别分类器:扬声器识别系统(文本独立)和一个孤立的单词识别系统(扬声器独立)。孤立的单词识别系统被构造为三个分类器的融合,一个用于第一个密码的每个单词。第一步的目的是通过组合两个识别分类器的结果来识别与第一个密码对应的耦合扬声器/密码。然后在第二个密码上应用验证系统,以确认或体现由上面的融合给出的识别结果(扬声器标识)。与艺术扬声器识别系统(文本相关)的状态相比,给出了4.76%的eer,所提出的系统的第一步提供了0.38%的eer,而第二步是文本独立验证的eer 0.26%的eer为0.26%文本依赖验证的0.13%。

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