Ordered rules for full sentence translation: A neural network realization and a case study for Hindi and English

摘要

As a general tool for pattern recognition, neural networks have made an impact in various fields which require automation and learning. Their use is demonstrated for learning ordered rules which make it possible to translate one language into another. Using pattern recognition techniques, it is shown that neural networks can implement such rules by learning to reorder the words in a sentence appropriately. First it is described how the ordered rules yield a situational translation from one language to another. Illustrative examples are given in English and Hindi, two Indo-European languages. Then the neural network realization of the translation algorithm is discussed. The work presented here may serve as a model for other languages.