Machine translation techniques
First Claim
1. A machine translation decoding method comprising:
- receiving as input a text segment in a source language to be translated into a target language;
generating an initial translation as a current target language translation;
applying one or more modification operators to the current target language translation to generate one or more modified target language translations;
determining whether one or more of the modified target language translations represents an improved translation in comparison with the current target language translation;
setting a modified target language translation as the current target language translation; and
repeating said applying, said determining and said setting until occurrence of a termination condition.
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Abstract
Machine translation decoding is accomplished by receiving as input a text segment in a source language to be translated into a target language, generating an initial translation as a current target language translation, applying one or more modification operators to the current target language translation to generate one or more modified target language translations, determining whether one or more of the modified target language translations represents an improved translation in comparison with the current target language translation, setting a modified target language translation as the current target language translation, and repeating these steps until occurrence of a termination condition. Automatically generating a tree (e.g., either a syntactic tree or a discourse tree) can be accomplished by receiving as input a tree corresponding to a source language text segment, and applying one or more decision rules to the received input to generate a tree corresponding to a target language text segment.
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Citations
65 Claims
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1. A machine translation decoding method comprising:
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receiving as input a text segment in a source language to be translated into a target language;
generating an initial translation as a current target language translation;
applying one or more modification operators to the current target language translation to generate one or more modified target language translations;
determining whether one or more of the modified target language translations represents an improved translation in comparison with the current target language translation;
setting a modified target language translation as the current target language translation; and
repeating said applying, said determining and said setting until occurrence of a termination condition. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 28, 29, 30, 31, 32, 33, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54)
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15. A computer-implemented machine translation decoding method comprising iteratively modifying a target language translation of a source language text segment until an occurrence of a termination condition.
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27. A machine translation decoder comprising:
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a decoding engine comprising one or more modification operators to be applied to a current target language translation to generate one or more modified target language translations; and
a process loop to iteratively modify the current target language translation using the one or more modification operators, the process loop terminating upon occurrence of a termination condition.
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34. A computer-implemented tree generation method comprising:
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receiving as input a tree corresponding to a source language text segment; and
applying one or more decision rules to the received input to generate a tree corresponding to a target language text segment.
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- 55. A computer-implemented tree generation module comprising a predetermined set of decision rules that when applied to a tree corresponding to a source language text segment generate a tree corresponding to a target language text segment.
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62. A method of determining a transfer function between trees of different types, the method comprising:
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generating a training set comprising a plurality of tree pairs and a mapping between each tree pair, each tree pair comprises a source tree and a corresponding target tree;
generating a plurality of learning cases by determining, for each tree pair, a sequence of operations that result in the target tree when applied to the source tree; and
generating a plurality of decision rules by applying a learning algorithm to the plurality of learning cases. - View Dependent Claims (63)
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64. A computer-implemented discourse-based machine translation system comprising:
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a discourse parser that parses the discourse structure of a source language text segment and generates a source language discourse tree for the text segment;
a discourse-structure transfer module that accepts the source language discourse tree as input and generates as output a target language discourse tree; and
a mapping module that maps the target language discourse tree into a target text segment. - View Dependent Claims (65)
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Specification