Improvement of likelihood ratio measurement in a forensic speaker identification based on Bayesian statistics

在法医学领域，为了帮助法官做出正确的判断，对犯罪嫌疑人构成犯罪的可能性程度进行显示是非常重要的。为了显示这种可能性，基于贝叶斯统计的似然比被广泛使用。近年来，利用该似然比进行法医说话人识别的研究也越来越多。然而，传统的方法只使用了给定语音数据的一部分。在本研究中，我提出了可以在不使给定语音数据无用的情况下使用的似然比测量方法，并证实了使用它的有效性

In the forensic science field, in order to help the suitable judgment by judges, it is important to show the degree of a possibility that a suspected person is a criminal. In order to show this possibility, the likelihood ratio based on Bayesian statistics is used widely. In recent years, research which uses this likelihood ratio for forensic speaker recognition is carried out. However, by the conventional method, only a part of the given speech data is used. In this study, I proposed the likelihood ratio measurement which can be used without making useless the given speech data, and confirmed the effectiveness of using it