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Improved statistical alignment models
Open accessAbstract
In this paper, we present and compare various single-word based alignment models for statistical machine translation. We discuss the five IBM alignment models, the Hidden-Markov alignment model, smoothing techniques and various modifications. We present different methods to combine alignments. As evaluation criterion we use the quality of the resulting Viterbi alignment compared to a manually produced reference alignment. We show that models with a first-order dependence and a fertility model lead to significantly better results than the simple models IBM-1 or IBM-2, which are not able to go beyond zero-order dependencies.
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Cited by
Unsupervised construction of large paraphrase corpora: exploiting massively parallel news sources
Dolan, B., Quirk, C., & Brockett, C. (2004) · Proceedings of the 20th international conference on Computational Linguistics - COLING '04 · doi:10.3115/1220355.1220406 · Cited by 728
Neural Machine Translation with Supervised Attention
Liu, L., Utiyama, M., Finch, A., & Sumita, E. (2016) · arXiv · doi:10.48550/arxiv.1609.04186 · Cited by 146
Jointly Learning to Align and Translate with Transformer Models
Garg, S., Peitz, S., Nallasamy, U., & Paulik, M. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) · doi:10.18653/v1/d19-1453 · Cited by 123
(2016) · doi:10.18653/v1/n16-1046 · Cited by 94
Rationales for Sequential Predictions
Vafa, K., Deng, Y., Blei, D., & Rush, A. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/2021.emnlp-main.807 · Cited by 14
Metadata
- Authors
- Och, F. J., & Ney, H.
- Venue
- Proceedings of the 38th Annual Meeting on Association for Computational Linguistics - ACL '00
- Published
- 2000
- Pages
- 440-447
- OpenAlex
- W1973923101
- Cited by
- 1,001
- References
- 0
- FWCI
- 23.67
- Type
- conference paper
- Language
- en
- Open access
- bronze
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