Using high-level linguistic knowledge for Chinese speech recognition

Dongxin Xu, Peiji Zhu, Taiyi Huang, D. Chen
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Abstract

A linguistic processor using syntactic, semantic and vocabulary knowledge as constraints to improve the performance of a Chinese speech recognition system is described. The processor can accept not only sentences but also phrases and words as speech input. Some characteristics of Chinese are taken into account and a knowledge representation framework based on a case frame is developed. Affirmative, negative, interrogative and elliptical sentences, etc., can be represented easily in this framework. The parsing algorithm, having no direct relation to tasks, depends only on the knowledge-representation form. Consequently, it is convenient to change the task-domain by the aid of knowledge acquisition tools. The processor can also distinguish Chinese homonymic characters.<>
运用高级语言知识进行中文语音识别
介绍了一种以句法、语义和词汇知识为约束的语言处理器,以提高汉语语音识别系统的性能。该处理器不仅可以接受句子,还可以接受短语和单词作为语音输入。考虑到汉语的特点,提出了一种基于案例框架的知识表示框架。肯定句、否定句、疑问句、省略句等都可以很容易地在这个框架中表示出来。解析算法与任务没有直接关系,只依赖于知识表示形式。因此,在知识获取工具的帮助下,可以方便地改变任务域。该处理器还能识别同音汉字。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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