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Nguyen, A.-D. Vo, J.-C. Shin, P. Tran, and C.-Y. Ock, \u201cBuilding a Korean-Vietnamese neural machine translation system with Korean morphological analysis and word sense disambiguation,\u201d IEEE Access, pp.1-13, 2019.","DOI":"10.1109\/ACCESS.2019.2902270"},{"key":"2","doi-asserted-by":"crossref","unstructured":"[2] Q.-P. Nguyen, A.-D. Vo, J.-C. Shin, and C.-Y. Ock, \u201cNeural Machine Translation Enhancements through Lexical Semantic Network,\u201d Proc. 10th International Conference on Computer Modeling and Simulation-ICCMS 2018, Sydney, Australia, pp.105-109, 2018. 10.1145\/3177457.3177461","DOI":"10.1145\/3177457.3177461"},{"key":"3","doi-asserted-by":"crossref","unstructured":"[3] G. Klein, Y. Kim, Y. Deng, J. Senellart, and A. Rush, \u201cOpenNMT: Open-Source Toolkit for Neural Machine Translation,\u201d Proc. 55th Annual Meeting of the Association for Computational Linguistics, Vancouver, Canada, pp.67-72, July 2017. 10.18653\/v1\/p17-4012","DOI":"10.18653\/v1\/P17-4012"},{"key":"4","doi-asserted-by":"crossref","unstructured":"[4] S.W. Cho, E.-H. Lee, and J.-H. Lee, \u201cPhrase-Level Grouping for Lexical Gap Resolution in Korean-Vietnamese SMT,\u201d in Computational Linguistics, vol.781, K. Hasida and W.P. Pa, eds. Springer Singapore, Singapore, pp.127-136, 2018. 10.1007\/978-981-10-8438-6_11","DOI":"10.1007\/978-981-10-8438-6_11"},{"key":"5","unstructured":"[5] Q.-P. Nguyen, J.-C. Shin, and C.-Y. Ock, \u201cKorean morphological analysis for Korean-Vietnamese statistical machine translation,\u201d J. Electron. Sci. Technol., vol.5, no.4, pp.413-419, Dec. 2017."},{"key":"6","unstructured":"[6] S.-W. Cho, Y.-G. Kim, H.-S. Kwon, E.-H. Lee, W.-K. Lee, H.-M. Cho, and J.-H. Lee, \u201cEmbedded clause extraction and restoration for the performance enhancement in Korean-Vietnamese statistical machine translation,\u201d Proc. 28th Annual Conference on Human &amp; Cognitive Language Technology, Busan, Korea, pp.280-284, 2016."},{"key":"7","doi-asserted-by":"crossref","unstructured":"[7] L. Bentivogli, A. Bisazza, M. Cettolo, and M. Federico, \u201cNeural versus Phrase-Based Machine Translation Quality: a Case Study,\u201d Proc. 2016 Conference on Empirical Methods in Natural Language Processing, Austin, Texas, pp.257-267, 2016. 10.18653\/v1\/d16-1025","DOI":"10.18653\/v1\/D16-1025"},{"key":"8","unstructured":"[8] M. Junczys-Dowmunt, T. Dwojak, and H. Hoang, \u201cIs neural machine translation ready for deployment? A case study on 30 translation directions,\u201d arXiv:1610.01108 [cs], Oct. 2016."},{"key":"9","doi-asserted-by":"crossref","unstructured":"[9] N. Ueffing and H. Ney, \u201cUsing POS information for statistical machine translation into morphologically rich languages,\u201d Proc. 10th conference on European chapter of the Association for Computational Linguistics, Budapest, Hungary, vol.1, pp.347-354, 2003. 10.3115\/1067807.1067853","DOI":"10.3115\/1067807.1067853"},{"key":"10","doi-asserted-by":"crossref","unstructured":"[10] Y. Belinkov, N. Durrani, F. Dalvi, H. Sajjad, and J. Glass, \u201cWhat do Neural Machine Translation Models Learn about Morphology?,\u201d Proc. 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Vancouver, Canada, pp.861-872, July 2017. 10.18653\/v1\/p17-1080","DOI":"10.18653\/v1\/P17-1080"},{"key":"11","doi-asserted-by":"crossref","unstructured":"[11] J. Niehues and E. Cho, \u201cExploiting linguistic resources for neural machine translation using multi-task learning,\u201d arXiv:170800993 Cs, Aug. 2017.","DOI":"10.18653\/v1\/W17-4708"},{"key":"12","unstructured":"[12] R.C. Balabantaray, \u201cName entity recognition in machine translation,\u201d Emerg. Technol., vol.1, no.3, p.3, 2010."},{"key":"13","doi-asserted-by":"crossref","unstructured":"[13] D. Bhalla, N. Joshi, and I. Mathur, \u201cImproving the quality of MT output using novel name entity translation scheme,\u201d Proc. 2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Mysore, India, pp.1548-1553, 2013. 10.1109\/icacci.2013.6637410","DOI":"10.1109\/ICACCI.2013.6637410"},{"key":"14","unstructured":"[14] H.-P. Le, \u201cVietnamese named entity recognition using token regular expressions and bidirectional inference,\u201d arXiv:161005652 Cs, Oct. 2016."},{"key":"15","unstructured":"[15] H.T. Le, R.C. Sam, H.C. Nguyen, and T.T. Nguyen, \u201cNamed entity recognition in vietnamese text using label propagation,\u201d Proc. 2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR), Hanoi, Vietnam, pp.366-370, Dec. 2013. 10.1109\/socpar.2013.7054160"},{"key":"16","doi-asserted-by":"crossref","unstructured":"[16] A.-D. Nguyen, K.-H. Nguyen, and V.-V. Ngo, \u201cNeural sequence labeling for Vietnamese POS tagging and NER,\u201d arXiv:181103754 Cs, Nov. 2018.","DOI":"10.1109\/RIVF.2019.8713710"},{"key":"17","doi-asserted-by":"publisher","unstructured":"[17] R. Chopra, N. Singh, Y. Zhenning, and N.Ch.S.N. Iyengar, \u201cSequence Labeling using Conditional Random Fields,\u201d Int. J. U-E-Serv. Sci. Technol., vol.10, no.9, pp.101-108, Sept. 2017. 10.14257\/ijunesst.2017.10.9.10","DOI":"10.14257\/ijunesst.2017.10.9.10"},{"key":"18","unstructured":"[18] A. Krogh, \u201cHidden Markov models for labeled sequences,\u201d Proc. 12th IAPR International Conference on Pattern Recognition (Cat. 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Xu, \u201cEnd-to-end learning of semantic role labeling using recurrent neural networks,\u201d Proc. 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), Beijing, China, pp.1127-1137, 2015. 10.3115\/v1\/p15-1109","DOI":"10.3115\/v1\/P15-1109"},{"key":"22","doi-asserted-by":"crossref","unstructured":"[22] C.N. dos Santos and V. Guimar\u00e3es, \u201cBoosting named entity recognition with neural character embeddings,\u201d arXiv:150505008 Cs, May 2015.","DOI":"10.18653\/v1\/W15-3904"},{"key":"23","doi-asserted-by":"crossref","unstructured":"[23] G. Lample, M. Ballesteros, S. Subramanian, K. Kawakami, and C. Dyer, \u201cNeural Architectures for Named Entity Recognition,\u201d Proc. 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, San Diego, California, pp.260-270, June 2016. 10.18653\/v1\/n16-1030","DOI":"10.18653\/v1\/N16-1030"},{"key":"24","doi-asserted-by":"publisher","unstructured":"[24] S. Hochreiter and J. Schmidhuber, \u201cLong Short-Term Memory,\u201d Neural Comput., vol.9, no.8, pp.1735-1780, Nov. 1997. 10.1162\/neco.1997.9.8.1735","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"25","unstructured":"[25] M.A. Casta\u00f1o, F. Casacuberta, and E. Vidal, \u201cMachine translation using neural networks and finite-state models,\u201d Proc. 7th International Conference on Theoretical and Methodological Issues in Machine Translation, Santa Fe, USA, pp.160-167, 1997."},{"key":"26","doi-asserted-by":"crossref","unstructured":"[26] M.L. Forcada and R.P. \u00d1eco, \u201cRecursive hetero-associative memories for translation,\u201d Proc. Biological and Artificial Computation: From Neuroscience to Technology, Berlin, Heidelberg, vol.1240, pp.453-462, 1997. 10.1007\/bfb0032504","DOI":"10.1007\/BFb0032504"},{"key":"27","unstructured":"[27] I. Sutskever, O. Vinyals, and Q.V. Le, \u201cSequence to sequence learning with neural networks,\u201d Proc. 27th Advances in Neural Information Processing Systems, Montreal, Canada, pp.3104-3112, 2014."},{"key":"28","doi-asserted-by":"crossref","unstructured":"[28] K. Cho, B. van Merrienboer, C. Gulcehre, D. Bahdanau, F. Bougares, H. Schwenk, and Y. Bengio, \u201cLearning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation,\u201d Proc. 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), Doha, Qatar, pp.1724-1734, Oct. 2014. 10.3115\/v1\/d14-1179","DOI":"10.3115\/v1\/D14-1179"},{"key":"29","unstructured":"[29] D.Q. Nguyen, D.Q. Nguyen, T. Vu, M. Dras, and M. Johnson, \u201cA fast and accurate Vietnamese word segmenter,\u201d Proc. 7th International Conference on Language Resources and Evaluation,Miyazaki, Japan, p.6, May 2018."},{"key":"30","doi-asserted-by":"crossref","unstructured":"[30] K. Papineni, S. Roukos, T. Ward, and W.-J. Zhu, \u201cBLEU: a method for automatic evaluation of machine translation,\u201d Proc. 40th Annual Meeting on Association for Computational Linguistics,Philadelphia, Pennsylvania, pp.311-318, 2001. 10.3115\/1073083.1073135","DOI":"10.3115\/1073083.1073135"},{"key":"31","unstructured":"[31] M. Snover, B. Dorr, R. Schwartz, L. Micciulla, and J. Makhoul, \u201cA study of translation edit rate with targeted human annotation,\u201d Proc. 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