N-gram distribution based language model adaptation

@inproceedings{Gao2000NgramDB,
  title={N-gram distribution based language model adaptation},
  author={Jianfeng Gao and Mingjing Li and Kai-Fu Lee},
  booktitle={INTERSPEECH},
  year={2000}
}
This paper presents two techniques for language model (LM) adaptation. The first aims to build a more general LM. We propose a distribution-based pruning of n-gram LMs, where we prune n-grams that are likely to be infrequent in a new document. Experimental results show that the distribution-based pruning method performed up to 9% (word perplexity reduction) better than conventional cutoff methods. Moreover, the pruning method results in a more general ngram backoff model, in spite of the domain… CONTINUE READING

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