The TAO of ATWV: Probing the mysteries of keyword search performance

S. Wegmann, Arlo Faria, Adam L. Janin, K. Riedhammer, N. Morgan
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引用次数: 47

Abstract

In this paper we apply diagnostic analysis to gain a deeper understanding of the performance of the the keyword search system that we have developed for conversational telephone speech in the IARPA Babel program. We summarize the Babel task, its primary performance metric, “actual term weighted value” (ATWV), and our recognition and keyword search systems. Our analysis uses two new oracle ATWV measures, a bootstrap-based ATWV confidence interval, and includes a study of the underpinnings of the large ATWV gains due to system combination. This analysis quantifies the potential ATWV gains from improving the number of true hits and the overall quality of the detection scores in our system's posting lists. It also shows that system combination improves our systems' ATWV via a small increase in the number of true hits in the posting lists.
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ATWV的TAO:探索关键字搜索性能的奥秘
在本文中,我们应用诊断分析来更深入地了解我们在IARPA巴别塔计划中为会话电话语音开发的关键字搜索系统的性能。我们总结了Babel任务,它的主要性能指标,“实际术语加权值”(ATWV),以及我们的识别和关键字搜索系统。我们的分析使用了两个新的oracle ATWV度量,一个基于引导的ATWV置信区间,并包括对由于系统组合而产生的大ATWV增益的基础的研究。该分析量化了通过提高真实命中次数和系统发布列表中检测分数的整体质量而获得的潜在ATWV收益。它还表明,系统组合通过在张贴列表中增加真实命中数来提高系统的ATWV。
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