Statistical alignment models for translational equivalence

@inproceedings{Zhao2007StatisticalAM,
  title={Statistical alignment models for translational equivalence},
  author={Bing Zhao},
  year={2007}
}
The ever-increasing amount of parallel data opens a rich resource to multilingual natural language processing, enabling models to work on various translational aspects like detailed human annotations, syntax and semantics. With efficient statistical models, many cross-language applications have seen significant progresses in recent years, such as statistical machine translation, speech-to-speech translation, cross-lingual information retrieval and bilingual lexicography. However, the current… CONTINUE READING

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