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Randomized Language Models via Perfect Hash Functions

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At this session of the NLIP Reading Group we’ll be discussing the following paper:

David Talbot and Thorsten Brants. 2008. Randomized Language Models via Perfect Hash Functions. In Proceedings of ACL -08.

Abstract: We propose a succinct randomized language model which employs a perfect hash function to encode fingerprints of n-grams and their associated probabilities, backoff weights, or other parameters. The scheme can represent any standard n-gram model and is easily combined with existing model reduction techniques such as entropy-pruning. We demonstrate the space-savings of the scheme via machine translation experiments within a distributed language modeling framework.

This talk is part of the Natural Language Processing Reading Group series.

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