• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Carnahan Conference on Security Technology >Effectiveness in open-set speaker identification
【24h】

Effectiveness in open-set speaker identification

机译：开放式说话人识别的有效性

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This paper presents investigations into the relative effectiveness of two alternative approaches to open-set text-independent speaker identification (OSTI-SI). The methods considered are the recently introduced i-vector and the more traditional GMM-UBM method supported by score normalisation. The study is motivated by the growing need for effective extraction of intelligence and evidence from audio recordings in the fight against crime. OSTI-SI is known to be the most challenging subclass of speaker recognition, and its adoption in criminal investigation applications is further complicated by undesired variations in speech characteristics due to changing levels of environmental noise. In this study, the experimental investigations are conducted using a protocol developed for the identification task, based on the NIST speaker recognition evaluation corpus of 2008. In order to closely cover relevant conditions in the considered application areas and investigate the identification performance in such scenarios, the speech data is contaminated with a range of real-world noise. The paper provides a detailed description of the experimental study and presents a thorough analysis of the results.
机译：本文介绍了两种开放式文本无关的说话人识别（OSTI-SI）替代方法的相对有效性的研究。考虑的方法是最近引入的i-vector和得分归一化支持的更传统的GMM-UBM方法。这项研究的动机是，在打击犯罪的过程中，越来越需要从录音中有效提取情报和证据。 OSTI-SI是说话人识别中最具挑战性的子类，由于环境噪声水平的变化，语音特征发生了不希望有的变化，使OSTI-SI在刑事调查应用中的应用更加复杂。在这项研究中，实验研究是基于2008年NIST说话者识别评估语料库，使用针对识别任务而开发的协议进行的。为了紧密涵盖所考虑的应用领域中的相关条件并调查在这种情况下的识别性能，语音数据受到一系列实际噪声的污染。本文提供了对实验研究的详细描述，并对结果进行了全面的分析。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号