An n-gram language model can also be shrunk by pruning, for example only storing n-grams with counts greater than some threshold (such as the count threshold of 40 used for the Google n-gram release) or using entropy to prune less-important n-grams (Stolcke, 1998) . Another option is to build approximate language models using techniques like Bloom filters (Talbot and Osborne 2007, Church et al. 2007) .