Randomized Language Models via Perfect Hash Functions
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If you have a question about this talk, please contact Diarmuid Ó Séaghdha.
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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