N-gram Distribution Based Language Model Adaptation

摘要

This paper presents two techiques 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 mehtod performed up to 9