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CHINESE LARGE-VOCABULARY NAME RECOGNITION SYSTEM USING CHARACTER DESCRIPTION AND SYLLABLE SPELLING RECOGNITION

机译:基于字符描述和音节拼写识别的中文大词汇名识别系统

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摘要

The large-vocabulary name recognition technique is one of the challenging tasks in the application of Chinese speech recognition technology. It can be applied on long-list automatic attendant systems and automatic directory assistance systems. A Chinese name has usually two to three characters with each character pronounced as a single syllable. It is a high perplexity task to recognize a word from a long-list of candidates, like more than three hundred thousand unique names in our experiments, given a very short utterance like one to two seconds of speech. Two novel approaches under an interactive framework are proposed in this paper to aid the recognition of a Chinese name: Character Description Recognition (CDR) and Syllable Spelling Recognition (SSR). Together with our robust finite-state recognizer given a graph-structured syllable lexicon for the full names, we achieved a very promising name recognition success rate, 94.5%, in our system-initiative dialogue system.
机译:大词汇名称识别技术是汉语语音识别技术应用中的一项艰巨任务。它可以应用于长列表自动助理系统和自动目录协助系统。中文名称通常有两到三个字符,每个字符发音为一个音节。在很短的说话时间(如一到两秒钟的语音)下,从一长串候选单词中识别一个单词(例如我们的实验中超过三十万个唯一名称)是一个高难度的任务。在交互式框架下,本文提出了两种新颖的方法来帮助识别中文名称:字符描述识别(CDR)和音节拼写识别(SSR)。与我们强大的有限状态识别器一起为全名提供图形结构的音节词典,我们在系统启动的对话系统中实现了非常有希望的名识别成功率94.5%。

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