Canonical and Surface Morphological Segmentation for Nguni Languages-Reference-Cited by-同舟云学术

Canonical and Surface Morphological Segmentation for Nguni Languages

Published:2022 Issue: Volume: Page:125-139
ISSN:1865-0929
Container-title:Artificial Intelligence Research
language:
Short-container-title:

Author:

Moeng Tumi,Reay Sheldon,Daniels Aaron,Buys Jan

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-95070-5_9

Reference23 articles.

1. Bahdanau, D., Cho, K., Bengio, Y.: Neural machine translation by jointly learning to align and translate. In: International Conference on Learning Representations (2015)

2. Bosch, S.E., Pretorius, L.: A computational approach to Zulu verb morphology within the context of lexical semantics. Lexikos 27, 152–182 (2017). http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S2224-00392017000100007&nrm=iso

3. Cotterell, R., Müller, T., Fraser, A., Schütze, H.: Labeled morphological segmentation with semi-Markov models. In: Proceedings of the Nineteenth Conference on Computational Natural Language Learning, pp. 164–174. Association for Computational Linguistics, Beijing (2015). https://doi.org/10.18653/v1/K15-1017. https://www.aclweb.org/anthology/K15-1017

4. Cotterell, R., Vieira, T., Schütze, H.: A joint model of orthography and morphological segmentation. In: Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 664–669. Association for Computational Linguistics, San Diego (2016). https://doi.org/10.18653/v1/N16-1080. https://www.aclweb.org/anthology/N16-1080

5. Creutz, M., et al.: Morph-based speech recognition and modeling of out-of-vocabulary words across languages. ACM Trans. Speech Lang. Process. (TSLP) 5(1), 1–29 (2007)

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Parsing IsiZulu Text Using Grammatical Framework;Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference;2023