Paper Info
Title
Score distribution based term specific thresholding for spoken term detection
Abstract
The spoken term detection (STD) task aims to return relevant segments from a spoken archive that contain the query terms. This paper focuses on the decision stage of an STD system. We propose a term specific thresholding (TST) method that uses per query posterior score distributions. The STD system described in this paper indexes word-level lattices produced by an LVCSR system using Weighted Finite State Transducers (WFSTs). The target application is a sign dictionary where precision is more important than recall. Experiments compare the performance of different thresholding techniques. The proposed approach increases the maximum precision attainable by the system.
Year
Venue
Keywords
2009
HLT-NAACL (Short Papers)
term detection,term specific thresholding,std system,paper indexes word-level lattice,query term,maximum precision,lvcsr system,different thresholding technique,weighted finite state transducers,query posterior score distribution
Field
DocType
Citations 
Pattern recognition,Computer science,Speech recognition,Finite state,Artificial intelligence,Natural language processing,Thresholding,Recall,Machine learning
Conference
2
PageRank 
References 
Authors
0.35
3
2
Name
Order
Citations
PageRank
Dogan Can112810.64
Murat Saraçlar221215.10