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首页> 外文会议>International Conference on Computational Linguistics and Intelligent Text Processing(CICLing 2006); 20060219-25; Mexico City(MX) >Information Retrieval from Spoken Documents
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Information Retrieval from Spoken Documents

机译：从口头文件中检索信息

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摘要

This paper describes a designed and implemented system for efficient storage, indexing and search in collections of spoken documents that takes advantage of automatic speech recognition. As the quality of current speech recognizers is not sufficient for a great deal of applications, it is necessary to index the ambiguous output of the recognition, i. e. the acyclic graphs of word hypotheses — recognition lattices. Then, it is not possible to directly apply the standard methods known from text-based systems. The paper discusses an optimized indexing system for efficient search in the complex and large data structure that has been developed by our group. The search engine works as a server. The meeting browser JFerret, developed withing the European AMI project, is used as a client to browse search results.
机译：本文介绍了一种设计和实现的系统，该系统可利用自动语音识别功能有效地存储，索引和搜索口述文件集合中的内容。由于当前语音识别器的质量不足以用于大量应用，因此有必要对识别的歧义输出进行索引，即e。单词假设的无环图-识别格。这样，就不可能直接应用基于文本的系统中已知的标准方法。本文讨论了由我们小组开发的，用于在复杂和大型数据结构中进行有效搜索的优化索引系统。搜索引擎充当服务器。与欧洲AMI项目一起开发的会议浏览器JFerret用作客户端浏览搜索结果。

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