Paper Info
Title
Voice-based Local Search Using a Language Model Look-ahead Structure for Efficient Pruning
Abstract
On mobile terminals, voice-based local search services are quickly becoming a new important application. Voice search is essentially a large vocabulary speech recognition task with an open ended vocabulary, and this is a problem because speed and accuracy are essential for a good user experience. Fortunately when a user submits a local search query, contextual information such as the user's current position can be used for constraining the full search space. In this paper, we use local information and present a pruning algorithm based on a LMLA (Language Model Look-Ahead) tree, which can significantly improve both the speed and the accuracy of the voice search system.
Year
DOI
Venue
2011
10.1109/CIS.2011.83
CIS
Keywords
Field
DocType
good user experience,language model look-ahead,open ended vocabulary,efficient pruning,speech recognition,trees (mathematics),natural languages,vocabulary speech recognition task,vocabulary,contextual information,large vocabulary speech recognition,voice-based local search service,voice-based local search,mobile terminals,voice search system,language model look-ahead structure,pruning algorithm,language model look-ahead tree structure,full search space,language model look-ahead tree,voice search,local search query,pruning,local information,query processing,real time systems,indexes,speech,look ahead,user experience,local search,indexation,language model,accuracy
User experience design,Computer science,Beam search,Look-ahead,Natural language,Artificial intelligence,Local search (optimization),Vocabulary,Language model,Voice search,Machine learning
Conference
ISBN
Citations 
PageRank 
978-1-4577-2008-6
0
0.34
References 
Authors
5
4
Name
Order
Citations
PageRank
Yao Lu17713.40
Gang Liu2834.93
Wei Chen3213.95
Jesper Olsen4112.44