摘要
大词汇量连续语音识别系统的性能很大程度上取决于语音库的质量 ,而语音库设计的中心环节就是语料选取。但是传统语料选取方法往往考虑因素单一 ,不利于语音识别系统有效利用语言信息。本语音库的语料选取方法综合考虑了多种因素 :三音子覆盖率、三音子覆盖效率、三音子稀疏度、常用词分布等 ,并完全实现程序自动选取 ,充分利用了原始语料 ,使选取结果的信息量更加丰富。程序自动选取结果可以覆盖94 1%的三音子 ,75 4 %的最常用词 ,覆盖效率和稀疏度也比传统方法有了较大改善。
The performance of continuous speech recognition systems depends much on speech database. Text selection is the key step in designing of the speech database. Conventional text selection methods consider too few factors for the recognition systems to use linguistic information effectually. This paper describes a method which can select text automatically and consider multiple factors: triphone covering rate, triphone covering efficiency, triphone sparse rate and distribution of commonly used words, etc. The set of selected text covers 94.1% triphones, 75.4% most commonly used words, and also the covering rate and sparse rate are improved than that of conventional methods.
出处
《中文信息学报》
CSCD
北大核心
2003年第4期27-32,共6页
Journal of Chinese Information Processing
基金
国家自然科学基金资助项目 (6 0 172 0 5 5 )
国家"86 3"资助项目 (2 0 0 1AA114 181)
北京市自然科学基金资助项目 (40 0 2 0 12 )
