ELRA Conference on Language Resources and Evaluation '98:
Rapid Language Model Development for New Task Domains

Please download a copy of the paper by clicking here:
ELRA LREC '98 Paper in gzip'ed PostScript format (~34K).
ELRA LREC '98 Paper in PostScript format (not compressed) (~97K).

Abstract:

Data sparseness has been regularly indicted as the primary problem in statistical language modelling. We go one step further to consider the situation when no text data is available for the target domain. We present two techniques for building efficient language models quickly for new domains. The first technique is based on using a context-free grammar to generate a corpus of word collocations. The second is an adaptation technique based on using out-of-domain corpora to estimate target domain language models. We report results of successfully using these two techniques individually and in combination to build efficient models for a spontaneous speech recognition task in a medium-sized vocabulary domain.
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