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电子法医语音科学系统(EFS)核心软件工具alpha版本的验证。

Validations of an alpha version of the E Forensic Speech Science System (EFS) core software tools.

作者信息

Weber Philip, Enzinger Ewald, Labrador Beltrán, Lozano-Díez Alicia, Ramos Daniel, González-Rodríguez Joaquín, Morrison Geoffrey Stewart

机构信息

Forensic Data Science Laboratory, Aston University, Birmingham, UK.

Forensic Evaluation Ltd, Birmingham, UK.

出版信息

Forensic Sci Int Synerg. 2022 Mar 7;4:100223. doi: 10.1016/j.fsisyn.2022.100223. eCollection 2022.

Abstract

This paper reports on validations of an alpha version of the E Forensic Speech Science System (EFS) core software tools. This is an open-code human-supervised-automatic forensic-voice-comparison system based on x-vectors extracted using a type of Deep Neural Network (DNN) known as a Residual Network (ResNet). A benchmark validation was conducted using training and test data () that have previously been used to assess the performance of multiple other forensic-voice-comparison systems. Performance equalled that of the best-performing system with previously published results for the test set. The system was then validated using two different populations (male speakers of Australian English and female speakers of Australian English) under conditions reflecting those of a particular case to which it was to be applied. The conditions included three different sets of codecs applied to the questioned-speaker recordings (two mismatched with the set of codecs applied to the known-speaker recordings), and multiple different durations of questioned-speaker recordings. Validations were conducted and reported in accordance with the "Consensus on validation of forensic voice comparison".

摘要

本文报告了电子法医语音科学系统(EFS)核心软件工具alpha版本的验证情况。这是一个基于使用一种称为残差网络(ResNet)的深度神经网络(DNN)提取的x向量的开放代码、人工监督的自动法医语音比较系统。使用先前用于评估多个其他法医语音比较系统性能的训练和测试数据()进行了基准验证。对于测试集,该系统的性能与先前公布结果中表现最佳的系统相当。然后,在反映该系统应用的特定案件条件下,使用两个不同群体(澳大利亚英语男性说话者和澳大利亚英语女性说话者)对该系统进行了验证。这些条件包括应用于受询问者录音的三种不同编解码器集(其中两种与应用于已知说话者录音的编解码器集不匹配),以及受询问者录音的多种不同时长。验证是根据“法医语音比较验证共识”进行并报告的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8bc/8908042/07064540ac19/gr1.jpg

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