%Aigaion2 BibTeX export from Idiap Publications
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@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},
}