@inproceedings{7a66860535ea48e1b2729e19b5c91548,
title = "Mixed Embedding of XLM for Unsupervised Cantonese-Chinese Neural Machine Translation (Student Abstract)",
abstract = "Unsupervised Neural Machines Translation is the most ideal method to apply to Cantonese and Chinese translation because parallel data is scarce in this language pair. In this paper, we proposed a method that combined a modified cross-lingual language model and performed layer to layer attention on unsupervised neural machine translation. In our experiments, we observed that our proposed method does improve the Cantonese to Chinese and Chinese to Cantonese translation by 1.088 and 0.394 BLEU scores. We finally developed a web service based on our ideal approach to provide Cantonese to Chinese Translation and vice versa.",
author = "Wong, {Ka Ming} and Tsai, {Richard Tzong Han}",
note = "Publisher Copyright: Copyright {\textcopyright} 2022, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.; 36th AAAI Conference on Artificial Intelligence, AAAI 2022 ; Conference date: 22-02-2022 Through 01-03-2022",
year = "2022",
month = jun,
day = "30",
doi = "10.1609/aaai.v36i11.21677",
language = "???core.languages.en_GB???",
series = "Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022",
publisher = "Association for the Advancement of Artificial Intelligence",
pages = "13081--13082",
booktitle = "IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations",
}