期刊文献+

一个基于文本输入的口语对话系统的新的实现策略 被引量:3

A New Implementation Approach of Grammar Generation Tool for Text-based SDS
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摘要 口语对话系统(Spoken Dialogue Systems,SDS)现在已经越来越多地应用于实际生活之中,然而,当前对于普通人来说要开发处理英文对话的功能强大的系统通常很困难,而一些被人们提出的、不很复杂的,且能够比较容易开发SDS的方法其理解能力则受到了限制。在介绍并比较了以上所提到的一些方法之后,一个基于文本的自然语言的SDS工具包(被称为SDS Lite)将会被详细地介绍。我们的系统处理中文对话并使不仅是专家而且是普通人都很容易学习和开发他们自己的SDS。 Spoken Dialogue Systems (SDS) are now more and more used in real life. However, current powerful systems for dealing with English dialogue are usually difficult for lay people to create, while some less complicated methods proposed to create SDS easily are with less powerful understanding capability. After introducing and comparing the approaches mentioned above, a natural language text interface SINS toolkit, named SDS Lite, is described in detail. Our system deals with Chinese dialogue and makes it very easy for not only experts, but also lay people to learn and create their own SDS.
出处 《计算机科学》 CSCD 北大核心 2006年第11期205-209,共5页 Computer Science
关键词 口语对话系统 SDS LITE 上下文无关增强文法 语义抽取 Spoken dialogue systems, SINS lite, Enhanced context free grammar, Semantic extraction
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参考文献5

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同被引文献27

  • 1冯志伟.自然语言处理中的概率语法[J].当代语言学,2005,7(2):166-178. 被引量:10
  • 2王厚峰,王波.基于句子对齐的汉语句法结构推导的计算模型[J].软件学报,2007,18(3):538-546. 被引量:2
  • 3黄昌宁,赵海.中文分词十年回顾[J].中文信息学报,2007,21(3):8-19. 被引量:246
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  • 7Frederic Bechet, Allen L. Gorin, Jeremy H. Wright, et al. , Detecting and extracting named entities from spontarieous speech in a mixed- initiative spoken dialogue context: How May I Hel PYou? [J]. Speech Communication, 2004, 42(2) : 207 -225.
  • 8N. Gupta, Gokhan Tur, Dilek Z. Hakkani - Ttir, et al.. The AT&T spoken language understanding system [ J ]. IEEE Transactions on Audio, Speech and Language Processing, 2006, 14( 1 ): 213 -222.
  • 9Yulan He and Steve J. Young, Spoken language understanding using the Hidden Vector State Model [ J ]. Speech Communication, 2006, 48 (3 - 4) : 262 - 275.
  • 10Minwoo Jeong and Gary Geunbae Lee. Triangular- Chain Conditional Random Fields [ J]. IEEE Transactions on Audio, Speech, and Language Processing, 2008, 16(7): 1287- 1302.

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