Posterior probability based indexing method for Chinese spoken document retrieval

被引：0

作者：

Zheng, Tie-Ran ^{[1
]}

Han, Ji-Qing ^{[1
]}

机构：

[1] School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China

来源：

Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology | 2009年 / 41卷 / 08期

关键词：

Information retrieval - Probability - Indexing (of information) - Speech recognition;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Syllable lattice based Chinese speech retrieval methods can avoid the problem of out of vocabulary (OOV) words and compensate the retrieval performance loss resulted by recognition error. For absence of effective indexing method in lattice based retrieval approaches, a posterior probability based indexing method is proposed in this paper, which introduces syllables and K step neighbor syllable pairs as index items and takes the posterior probability as weighted value for an improved vector space model. It is proven by a series of retrieval experiments that our method is more suitable for lattice based spoken document retrieval tasks and the improvement accomplishes its anticipated purposes.

引用

页码：97 / 102