Mismatching-aware unsupervised translation quality estimation for low-resource languages

Author:

Azadi FatemehORCID,Faili Heshaam,Dousti Mohammad Javad

Publisher

Springer Science and Business Media LLC

Reference51 articles.

1. Aldarmaki, H., & Diab, M. (2019). Context-aware cross-lingual mapping. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). Association for Computational Linguistics, Minneapolis, Minnesota, pp 3906–3911.

2. Banerjee, S., & Lavie, A. (2005). METEOR: An automatic metric for MT evaluation with improved correlation with human judgments. In: Proceedings of the ACL workshop on intrinsic and extrinsic evaluation measures for machine translation and/or summarization, pp 65–72.

3. Cao, S., Kitaev, N., & Klein, D. (2019). Multilingual alignment of contextual word representations. In: International Conference on Learning Representations.

4. Chen, Y., Su, C., & Zhang, Y. et al. (2021). HW-TSC’s participation at WMT 2021 quality estimation shared task. In: Proceedings of the Sixth Conference on Machine Translation, pp 890–896.

5. Conneau, A., & Lample, G. (2019). Cross-lingual language model pretraining. Advances in neural information processing systems 32.

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