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A Multi-layered Summarization System for Multi-media Archives by Understanding and Structuring of Chinese Spoken Documents

机译:通过理解和构造中文口语文献的多媒体档案多层汇总系统

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The multi-media archives are very difficult to be shown on the screen, and very difficult to retrieve and browse. It is therefore important to develop technologies to summarize the entire archives in the network content to help the user in browsing and retrieval. In a recent paper [1] we proposed a complete set of multi-layered technologies to handle at least some of the above issues: (1) Automatic Generation of Titles and Summaries for each of the spoken documents, such that the spoken documents become much more easier to browse, (2) Global Semantic Structuring of the entire spoken document archive, offering to the user a global picture of the semantic structure of the archive, and (3) Query-based Local Semantic Structuring for the subset of the spoken documents retrieved by the user's query, providing the user the detailed semantic structure of the relevant spoken documents given the query he entered. The Probabilistic Latent Semantic Analysis (PLSA) is found to be helpful. This paper presents an initial prototype system for Chinese archives with the functions mentioned above, in which the broadcast news archive in Mandarin Chinese is taken as the example archive.
机译:多媒体档案很难在屏幕上显示,也很难检索和浏览。因此,重要的是开发技术来总结网络内容中的整个档案,以帮助用户浏览和检索。在最近的一篇论文中[1],我们提出了一套完整的多层技术来处理至少一些上述问题:(1)自动为每个语音文档生成标题和摘要,从而使语音文档变得越来越多更易于浏览,(2)整个语音文档档案的全局语义结构,向用户提供档案语义结构的全局图片,以及(3)语音文档子集的基于查询的局部语义结构通过用户的查询检索,从而根据用户输入的查询向用户提供相关口头文件的详细语义结构。发现概率潜在语义分析(PLSA)是有帮助的。本文提出了具有上述功能的中文档案的初始原型系统,以普通话广播新闻档案为例。

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