Corpus ID: 44157913

A Survey of Domain Adaptation for Neural Machine Translation

@inproceedings{Chu2018ASO,
  title={A Survey of Domain Adaptation for Neural Machine Translation},
  author={Chenhui Chu and Rui Wang},
  booktitle={COLING},
  year={2018}
}
  • Chenhui Chu, Rui Wang
  • Published in COLING 2018
  • Computer Science
  • Neural machine translation (NMT) is a deep learning based approach for machine translation, which yields the state-of-the-art translation performance in scenarios where large-scale parallel corpora are available. Although the high-quality and domain-specific translation is crucial in the real world, domain-specific corpora are usually scarce or nonexistent, and thus vanilla NMT performs poorly in such scenarios. Domain adaptation that leverages both out-of-domain parallel corpora as well as… CONTINUE READING

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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 97 REFERENCES

    Domain Control for Neural Machine Translation

    VIEW 11 EXCERPTS
    HIGHLY INFLUENTIAL

    Effective Domain Mixing for Neural Machine Translation

    VIEW 6 EXCERPTS
    HIGHLY INFLUENTIAL

    On Using Monolingual Corpora in Neural Machine Translation

    VIEW 13 EXCERPTS
    HIGHLY INFLUENTIAL

    Neural Machine Translation by Jointly Learning to Align and Translate

    VIEW 10 EXCERPTS
    HIGHLY INFLUENTIAL