摘要
本文在大量语音实验的基础上,对汉语语音识别方法进行了较为深入的探讨,并以IBMPC/AT配以自行研制开发的TMS320C25-E型高速信号处理板为硬件基础,建立了一个特定人汉语普通话全音节实时识别系统.该系统针对汉语普通话的语音特点,采用了分层识别策略.整个系统响应时间小于0.2秒,用4遍1240个全音节语音对系统进行的严格测试表明:系统四声识别的平均正确率为99％左右,音节识别前5个候选的正确识别率分别为82％,91％,94％,96％,97％;同时,本文根据这一测试结果建立了相应的声韵母混淆矩阵和基于Shepard方法的相似度集群分析树图,并对照汉语语音合成清晰度测试结果及汉语语音知觉结构的集群分析结果,对本系统各部分进行了较为深入的分析,提出了相应的改进措施.
Based on a large number of speech experiments, Mandarin speech recognition approaches have been thoroughly studied, and a real-time speaker-dependent all-syllable recognition system of Mandarin has been developed on an IBM PC/AT microcomputer with a high-speed digital signal processing board TMS320C25-E. In accordance with the phonetic characteristics of Mandarin, the three-stage recognition strategy is adopted in this system. Experiments for the speech datas of 4 times 1240 syllables show that, average correct rate of four tone recognition is about 99%, correct rates of the first 5 candidates of syllable recognition are 82%, 91%, 94%, 96%, and 97% respectively, and the whole system response time is less than 0.2 second. In addition, the Mandarin initials and finals confusion matrices, and the corresponding hierarchical clustering diagram of the similarity are obtained from the experiment results, and they are analyzed in comparision with the references [1,2] so as to further improve the system performance.
出处
《声学学报》
EI
CSCD
北大核心
1993年第3期161-171,共11页
Acta Acustica
基金
国家自然科学基金资助项目
