Date of Original Version



Conference Proceeding

Journal Title

Proceedings of INTERSPEECH

First Page


Last Page


Rights Management

Copyright 2014 ISCA

Abstract or Description

Spoken Term Detection (STD) focuses on finding instances of a particular spoken word or phrase in an audio corpus. Most STD systems have a two-step pipeline, ASR followed by search. Two approaches to search are common, Confusion Network (CN) based search and Finite State Transducer (FST) based search. In this paper, we examine combination of these two different search approaches, using the same ASR output. We find that the CN search performs better on shorter queries, and FST search performs better on longer queries. By combining the different search results from the same ASR decoding, we achieve better performance compared to either search approach on its own. We also find that this improvement is additive to the usual combination of decoder results using different modeling techniques.



Published In

Proceedings of INTERSPEECH, 2784-2788.