首页 | 本学科首页   官方微博 | 高级检索  
     

基于音位属性检测的PSPL改进方法
引用本文:陆明明,张连海,牛铜.基于音位属性检测的PSPL改进方法[J].信息工程大学学报,2012,13(4):426-431.
作者姓名:陆明明  张连海  牛铜
作者单位:信息工程大学 信息工程学院,河南郑州,450002
基金项目:国家自然科学基金资助项目
摘    要:为了提高PSPL(position specific posterior lattices)作为语音文档索引时的检索性能,提出一种基于音位属性检测的PSPL改进方法。该方法首先根据信源熵准则找出原始PSPL中不确定度较大的词弧集合,然后利用音位属性对这些词弧集合进行识别结果修正以及后验概率重估,从而实现对PSPL数据结构的改善。实验结果表明,改进后的PSPL在包含更多正确识别结果的同时,解决了后验概率取值不准确的问题,其解码性能和检索性能均优于原始PSPL。

关 键 词:语音文档检索  语音文档索引  PSPL  自动语音识别  音位属性检测

Improved Position Specific Posterior Lattices Based on Phonological Feature Detection
LU Ming-ming,ZHANG Lian-hai,NIU Tong.Improved Position Specific Posterior Lattices Based on Phonological Feature Detection[J].Journal of Information Engineering University,2012,13(4):426-431.
Authors:LU Ming-ming  ZHANG Lian-hai  NIU Tong
Affiliation:(Institute of Information Engineering, Information Engineering University, Zhengzhou 450002, China)
Abstract:In the research of spoken document indexing, an alternative position specific posterior lat-tices (PSPL) method based on phonological feature detection is proposed to promote the performance of retrieval. Following the information entropy principle, the sets with high uncertainty are firstly found out from the original PSPL, and then the modification of word arc recognition and revaluation of posterior probability are conducted based on phonological features, which improves the PSPL data structures. Experimental results show that more correct recognition results are delivered by the new PSPL, and the problem of incorrect posterior probability is also solved. Furthermore, better perform-ance in terms of decoding and retrieval is obtained compared with the original PSPL.
Keywords:spoken document retrieval  spoken document indexing  position specific posterior lat-tices  automatic speech recognition  phonological feature detection
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《信息工程大学学报》浏览原始摘要信息
点击此处可从《信息工程大学学报》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号