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Samvaadhana : A Telugu Dialogue System in Hospital Domain

机译:包括:Telugu对话系统伤害域名

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In this paper, a dialogue system for Hospital domain in Telugu, which is a resource-poor Dravidian language, has been built. It handles various hospital and doctor related queries. The main aim of this paper is to present an approach for modelling a dialogue system in a resource-poor language by combining linguistic and domain knowledge. Focusing on the question answering aspect of the dialogue system, we identified Question Classification and Query Processing as the two most important parts of the dialogue system. Our method combines deep learning techniques for question classification and computational rule-based analysis for query processing. Human evaluation of the system has been performed as there is no automated evaluation tool for dialogue systems in Telugu. Our system achieves a high overall rating along with a significantly accurate context-capturing method as shown in the results.
机译:在本文中,已经建立了泰卢固化的医院域对话系统,这是一种资源可怜的Dravidian语言。 它处理各种医院和医生相关的查询。 本文的主要目的是通过组合语言和域知识来提出一种用于以资源差的语言建模对话系统的方法。 专注于对话系统的问题回答方面,我们将问题分类和查询处理确定为对话系统的两个最重要的部分。 我们的方法结合了对问题分类的深度学习技术和基于计算规则的查询处理分析。 已经进行了对该系统的人类评估,因为Telugu的对话系统没有自动评估工具。 我们的系统达到了高总体评级,以及显着准确的上下文捕获方法,如结果所示。

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