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Word-dependent transition models in HMM based word alignment for statistical machine translation

  • US 20090112573A1
  • Filed: 10/30/2007
  • Published: 04/30/2009
  • Est. Priority Date: 10/30/2007
  • Status: Active Grant
First Claim
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1. A method for estimating an alignment between words in a source phrase and words in a target phrase, comprising:

  • providing at least one set of probabilistic word-dependent transition models, said word-dependent transition models having been automatically learned from at least one training data set comprising known parallel texts representing a source language and a target language;

    each word-dependent transition model representing a self-jump probability of a particular word in combination with probabilities of jumping from that word to other particular words;

    providing a source phrase in the source language and selecting a corresponding word-dependent transition model for each word in the source phrase;

    constructing a Hidden Markov Model (HMM) on the source phrase from the probabilistic word-dependent transition models for each word of the source phrase in combination with other HMM components including word emission models;

    evaluating the HMM to determine an alignment between the source phrase and a target phrase in the target language; and

    storing the alignment between the source phrase and the target phrase for later use.

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