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Randomized Language Models via Perfect Hash Functions

, и . Proceedings of ACL-08: HLT, стр. 505--513. Columbus, Ohio, Association for Computational Linguistics, (июня 2008)

Аннотация

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.

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