期刊文献+
共找到2篇文章
< 1 >
每页显示 20 50 100
A NOVEL SPACE-COMPRESSED CHINESE WORD DIGRAM BASED ON BI-CHARACTER CO-ARTICULATION FREQUENCY 被引量:1
1
作者 Zhao Yibao Qiao Liyan Tan Jianxun Sun Shenghe(Automatic Test and Control Department, Harbin Institute of Technology, Harbin 150001) (Robot Research Institute, Harbin Institute of Technology, Harbin 150001) 《Journal of Electronics(China)》 2000年第2期178-184,共7页
Chinese Phonetic-Character Conversion(CPCC) is an important issue in Chinese speech recognition and Chinese sentence keyboard input system. The approaches based on large corpus statistic Markov language model (such as... Chinese Phonetic-Character Conversion(CPCC) is an important issue in Chinese speech recognition and Chinese sentence keyboard input system. The approaches based on large corpus statistic Markov language model (such as bigram, trigram) become more and more popular today. This paper presents an improved Chinese word bigram, space-compressed Chinese word bigram, which stores the bi-word co-articulation frequency in the form of the bi-character co-articulation frequency. The bi-word co-articulation frequency is estimated from the bi-character co-articulation frequency library. The CPCC experiment with the improved Chinese word bigram shows: it can reach a higher correct conversion ratio with less space occupation. 展开更多
关键词 cpcc MARKOV model bigram WORD FREQUENCY ESTIMATE
下载PDF
一种基于单字统计二元文法的自组词音字转换算法 被引量:6
2
作者 赵以宝 孙圣和 《电子学报》 EI CAS CSCD 北大核心 1998年第10期55-59,共5页
音字转换在语音识别和汉字语句键盘输入方面都占有很重要的地位.现在比较流行的方法是基于大语料统计的Markov模型的音字转换方法其中基于单字N元文法的音字转换算法具有数据量少、算法简单的优点.但转换准确率却较低;而基于词N元文法... 音字转换在语音识别和汉字语句键盘输入方面都占有很重要的地位.现在比较流行的方法是基于大语料统计的Markov模型的音字转换方法其中基于单字N元文法的音字转换算法具有数据量少、算法简单的优点.但转换准确率却较低;而基于词N元文法的音字转换算法则正好相反本文在基于单字统计Bigram算法的基础上提出了一种自组词的音字转换方法,不仅具有单字Brgram方法的占空间少的优点.而且又可充分利用基于词Bigram算法的优点,实验表明该方法容易实现而且具有较高的转换准确率. 展开更多
关键词 音字转换 二元文法 自组词 语音识别
下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部