Paper Info
Title
Using statistical language modelling to identify new vocabulary in a grammar-based speech recognition system
Abstract
Spoken language recognition meets with difficulties when an unknown word is encountered. In addition to the new word being unrecognisable, its presence impacts on recognition per- formance on the surrounding words. The possibility is explored here of using a back-off statistical recogniser to allow rec og- nition of out-of-vocabulary words in a grammar-based speech recognition system. This study shows that a statistical lan guage model created from a corpus obtained using a grammar-based system and augmented with minimally-constrained domain- appropriate material allows extraction of words that are out of the vocabulary of the grammar in an unseen corpus with fairly high precision.
Year
Venue
Field
2003
INTERSPEECH
Speech corpus,Speech synthesis,Computer science,Computational linguistics,Grammar,Speech recognition,Natural language processing,Artificial intelligence,Language modelling,Vocabulary
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
7
1
Name
Order
Citations
PageRank
Genevieve Gorrell126622.00