N-gram weighting: reducing training data mismatch in cross-domain language model estimation

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In domains with insufficient matched training data, language models are often constructed by interpolating component models trained from partially matched corpora. Since the n-grams from such corpora may not be of equal relevance to the target domain, we propose an n-gram weighting technique to adjust the component n-gram probabilities ba...More