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

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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