Machine Learning Based Optimized Pruning Approach for Decoding in Statistical Machine Translation

@article{Banik2019MachineLB,
  title={Machine Learning Based Optimized Pruning Approach for Decoding in Statistical Machine Translation},
  author={Debajyoty Banik and Asif Ekbal and Pushpak Bhattacharyya},
  journal={IEEE Access},
  year={2019},
  volume={7},
  pages={1736-1751}
}
A conventional decoding algorithm is critical to the success of any statistical machine translation system. Providing an enormous amount of space leads to inappropriate slow decoding. There is a trade-off between the translation accuracy and the decoding speed. Pruning algorithms (like histogram pruning, threshold pruning) are trying to optimize this. The pruning algorithm has a pre-defined limit on the supplemental parameters (i.e. stack size, beam threshold) that helps to improve the… CONTINUE READING

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