文章基本信息

标题：BTH:an Efficient Parsing Algorithm for Keyword Spotting
本地全文：下载
作者：Takehide YANO ; Munehiko SASAJIMA ; Yasuyuki KONO 等
期刊名称：人工知能学会論文誌
印刷版ISSN：1346-0714
电子版ISSN：1346-8030
出版年度：2002
卷号：17
期号：6
页码：658-666
DOI：10.1527/tjsai.17.658
出版社：The Japanese Society for Artificial Intelligence
摘要：In this paper, we propose BTH, a parsing algorithm which is able to efficiently parse keyword lattice that contains large number of false candidates. In BTH, the grammar is written in template form, and then, it is compiled into a hash table. BTH analyzes the lattice without unfolding to keyword sequences, by propagating acceptable templates among the linked keywords and filtering through the hash table in each keywords. It has a time bound proportional to n² (where n is the number of keywords in the lattice), although the number of false candidates increases exponentially. Simulation results shows that BTH can parse lattice which contains over 100 billion false candidates within 0.35 sec, with grammar which is corresponding to 2 million of templates, on a notebook-PC(PentiumII 266MHz).
关键词：spoken dialogue system ; lattice parser