模拟零资源口语术语发现

Jerome White, Douglas W. Oard
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引用次数: 0

摘要

如果搜索引擎要索引世界上所有的口语内容,它们将需要处理数百种语言,而这些语言还没有自动语音识别系统存在。零资源口语术语发现,在某些声学表示中检测到重复内容,提供了一个潜在的有用的索引特征来源。本文描述了一个基于文本的零资源口语术语发现系统的模拟,该系统允许将任何信息检索测试集合用作信息检索技术早期开发的基础。提出这些技术以后可以应用于实际的零资源口语术语发现结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simulating Zero-Resource Spoken Term Discovery
If search engines are ever to index all of the spoken content in the world, they will need to handle hundreds of languages for which no automatic speech recognition systems exist. Zero-resource spoken term discovery, in which repeated content is detected in some acoustic representation, offers a potentially useful source of indexing features. This paper describes a text-based simulation of a zero-resource spoken term discovery system that allows any information retrieval test collection to be used as a basis for early development of information retrieval techniques. It is proposed that these techniques can be later applied to actual zero-resource spoken term discovery results.
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