Patent ReferencesMeans for resolving ambiguities in text based upon character context Text analysis system with letter sequence recognition and speech stress assignment arrangement Design and construction of a binary-tree system for language modelling Synthesizing word baseforms used in speech recognition Chart parser for stochastic unification grammar Method for language-independent text tokenization using a character categorization Method and apparatus for the automatic determination of phonological rules as for a continuous speech recognition system Method and means for grammatically processing a natural language sentence System for processing natural language including identifying grammatical rule and semantic concept of an undefined word Methods for part-of-speech determination and usage Inventors
AssigneeApplicationNo. 736278 filed on 07/25/1991US Classes:704/9, Natural language704/2Translation machineExaminersPrimary: Huntley, DavidAssistant: Kyle, Michael J. Attorney, Agent or FirmForeign Patent References
International ClassesG06F 017/20G06F 017/27 AbstractThe 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.Other References
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