Improved spoken query transcription using co-occurrence information

Spoken queries are a natural medium for searching the Mobile Web. Language modeling for voice search recognition offers different challenges compared to more conventional speech applications. The challenges arise from the fact that spoken queries are usually a set of keywords and do not have a syntactic and grammatical structure. This paper describes a cooccurrence based approach to improve the accuracy of voice queries automatic transcription. With the right choice of scoring function and co-occurrence level, we show that co-occurrence information gives a 2% relative accuracy improvement over a state of the art system. Copyright © 2011 ISCA.