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Weighted tree automata and transducers for syntactic natural language processing.

机译:加权树自动机和用于句法自然语言处理的转换器。

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摘要

Weighted finite-state string transducer cascades are a powerful formalism for models of solutions to many natural language processing problems such as speech recognition, transliteration, and translation. Researchers often directly employ these formalisms to build their systems by using toolkits that provide fundamental algorithms for transducer cascade manipulation, combination, and inference. However, extant transducer toolkits are poorly suited to current research in NLP that makes use of syntax-rich models. More advanced toolkits, particularly those that allow the manipulation, combination, and inference of weighted extended top-down tree transducers, do not exist. In large part, this is because the analogous algorithms needed to perform these operations have not been defined. This thesis solves both these problems, by describing and developing algorithms, by producing an implementation of a functional weighted tree transducer toolkit that uses these algorithms, and by demonstrating the performance and utility of these algorithms in multiple empirical experiments on machine translation data.
机译:加权有限状态字符串换能器级联是一种强大的形式化形式,用于解决许多自然语言处理问题(例如语音识别,音译和翻译)的解决方案模型。研究人员经常通过使用工具箱直接使用这些形式主义来构建他们的系统,该工具箱提供了用于换能器级联操纵,组合和推理的基本算法。但是,现存的换能器工具包不适合使用语法丰富的模型的NLP当前研究。不存在更高级的工具包,特别是那些允许对加权扩展的自上而下的树型换能器进行操作,组合和推断的工具包。在很大程度上,这是因为尚未定义执行这些操作所需的类似算法。本文通过描述和开发算法,通过生产使用这些算法的功能加权树换能器工具包的实现,以及通过在机器翻译数据的多次经验实验中展示这些算法的性能和实用性,解决了这两个问题。

著录项

  • 作者

    May, Jonathan David Louis.;

  • 作者单位

    University of Southern California.;

  • 授予单位 University of Southern California.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 231 p.
  • 总页数 231
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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