Method and system for natural language translation
First Claim
1. A method operating on a computer for translating source text from a first language to target text in a second language different from the first language, said method comprising the steps of:
- measuring a value of the source text in the firs language and storing the source text in a first memory buffer;
generating the target text in the second language based on a combination of a probability of occurrence of an intermediate structure of text associated with a target hypothesis selected from the second language using a target language model, and a probability of occurrence of the source text given the occurrence of said intermediate structure of text associated with said target hypothesis using a target-to-source translation model; and
performing at least one of a storing operation to save said target text in a second memory buffer and a presenting operation to make said target text available for at least one of a viewing and listening operation using an I/O device.
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Abstract
The present invention is a system for translating text from a first source language into a second target language. The system assigns probabilities or scores to various target-language translations and then displays or makes otherwise available the highest scoring translations. The source text is first transduced into one or more intermediate structural representations. From these intermediate source structures a set of intermediate target-structure hypotheses is generated. These hypotheses are scored by two different models: a language model which assigns a probability or score to an intermediate target structure, and a translation model which assigns a probability or score to the event that an intermediate target structure is translated into an intermediate source structure. Scores from the translation model and language model are combined into a combined score for each intermediate target-structure hypothesis. Finally, a set of target-text hypotheses is produced by transducing the highest scoring target-structure hypotheses into portions of text in the target language. The system can either run in batch mode, in which case it translates source-language text into a target language without human assistance, or it can function as an aid to a human translator. When functioning as an aid to a human translator, the human may simply select from the various translation hypotheses provided by the system, or he may optionally provide hints or constraints on how to perform one or more of the stages of source transduction, hypothesis generation and target transduction.
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Citations
42 Claims
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1. A method operating on a computer for translating source text from a first language to target text in a second language different from the first language, said method comprising the steps of:
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measuring a value of the source text in the firs language and storing the source text in a first memory buffer; generating the target text in the second language based on a combination of a probability of occurrence of an intermediate structure of text associated with a target hypothesis selected from the second language using a target language model, and a probability of occurrence of the source text given the occurrence of said intermediate structure of text associated with said target hypothesis using a target-to-source translation model; and performing at least one of a storing operation to save said target text in a second memory buffer and a presenting operation to make said target text available for at least one of a viewing and listening operation using an I/O device. - View Dependent Claims (2)
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3. A method operating on a computer for translating source text from a first language to target in a second language different from the first language, said method comprising the steps of:
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receiving the source text in the first language; generating at least one target hypothesis, each of said target hypotheses comprising text selected from the second language; estimating, for each target hypothesis, a first probability of occurrence of said text associated with said target hypothesis using a target language model; estimating, for each target hypothesis, a second probability of occurrence of the source text given the occurrence of said text associated with said target hypothesis using a target-to-source translation model; combining, for each target hypothesis, said first and second probabilities to produce a target hypothesis match score; and performing at least one of a storing operation to save and a presenting operation to make available for at least one of a viewing and listening operation, at least one of said target hypotheses according to its associated match score. - View Dependent Claims (4, 5, 6, 7, 8, 9)
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10. A method operating on a computer for translating source text from a first language to target text in a second language different from the first language, said method comprising the steps of:
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receiving the source text in the first language and storing the source text in a first memory buffer; receiving one of zero or more user defined criteria pertaining to the source and target texts to thereby bound the target text; accessing the source text from said first buffer and transducing the source text into at least one intermediate source structure of text constrained by any of said user defined criteria; generating at least one target hypothesis, each of said target hypotheses comprising an intermediate target structure of text selected from the second language constrained by any of said user defined criteria; estimating a first score, said first score being proportional to a probability of occurrence of each intermediate target structure of text associated with said target hypotheses using a target structure language model; estimating a second score, said second score being proportional to a probability that said intermediate target structure of text associated with said target hypotheses will translate into said intermediate source structure of text using a target structure-to-source structure translation model; combining, for each target hypothesis, said first and second scores to produce a target hypothesis match score; transducing each of said intermediate target structures of text into at least one transformed target hypothesis of text in the second language constrained by any of said user defined criteria; and performing at least one of a storing operation to save said at least one transformed target hypothesis in a second memory buffer and a presenting operation to make available for at least one of a viewing and listening operation according to its associated match score and said user defined criteria. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22)
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23. A computer system for translating source text from a first language to target text in a second language different from the first language, said system comprising:
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means for receiving the source text in the first language; means for generating at least one target hypothesis, each of said target hypotheses comprising text selected from the second language; means for estimating, for each target hypothesis, a first probability of occurrence of said text associated with said target hypothesis using a target language model; means for estimating, for each target hypothesis, a second probability of occurrence of the source text given the occurrence of said text associated with said target hypothesis using a target-to-source translation model; means for combining, for each target hypothesis, said first and second probabilities to produce a target hypothesis match score; and means for performing at least one of a storing and presenting operation to save or otherwise make available for at least one of a viewing and listening operation, at least one of said target hypotheses according to its associated match score. - View Dependent Claims (24, 25, 26, 27, 28, 29)
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30. A computer system for translating source text from a first language to target text in a second language different from the first language, said system comprising:
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means for receiving the source text in the first language and storing the source text in a first memory buffer; means for receiving one of zero or more user defined criteria pertaining to the source and target texts to thereby bound the target text; means for accessing the source text from said first buffer; first transducing means for transducing the source text into at least one intermediate source structure of text constrained by any of said user defined criteria; means for generating at least one target hypothesis, each of said target hypotheses comprising a intermediate target structure of text selected from the second language constrained by any of said user defined criteria; means for estimating a first score, said first score being proportional to a probability of occurrence of each intermediate target structure of text associated with said target hypotheses using a target structure language model; means for estimating a second score, said second score being proportional to a probability that said intermediate target structure of text associated with said target hypotheses will translate into said intermediate source structure of text using a target structure-to-source structure translation model; means for combining, for each target hypothesis, said first and second scores to produce a target hypothesis match score; second transducing means for transducing each of said intermediate target structures of text into at least one transformed target hypothesis of text in the second language constrained by any of said user defined criteria; and means for at least one of storing said at least one transformed target hypothesis in a second memory buffer, and presenting or otherwise making said at least one transformed target hypothesis available for at least one of a viewing and listening operation according to its associated match score and said user defined criteria. - View Dependent Claims (31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42)
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Specification