%Aigaion2 BibTeX export from Idiap Publications %Friday 13 December 2024 10:14:47 PM @TECHREPORT{McGreevy04a, author = {McGreevy, Michael}, projects = {Idiap}, title = {Pseudo-Syntactic Language Modeling for Disfluent Speech Recognition}, type = {Idiap-RR}, number = {Idiap-RR-55-2004}, year = {2004}, institution = {IDIAP}, note = {Published in Proceedings of SST, 2004}, abstract = {Language models for speech recognition are generally trained on text corpora. Since these corpora do not contain the disfluencies found in natural speech, there is a train/test mismatch when these models are applied to conversational speech. In this work we investigate a language model (LM) designed to model these disfluencies as a syntactic process. By modeling self-corrections we obtain an improvement over our baseline syntactic model. We also obtain a 30\\% relative reduction in perplexity from the best performing standard {N-gram} model when we interpolate it with our syntactically derived models.}, pdf = {https://publications.idiap.ch/attachments/reports/2004/rr04-55.pdf}, postscript = {ftp://ftp.idiap.ch/pub/reports/2004/rr04-55.ps.gz}, ipdmembership={speech}, }