论文标题
朝着神经机器翻译的Edoid语言
Towards Neural Machine Translation for Edoid Languages
论文作者
论文摘要
许多尼日利亚语言已将其以前的现代社会声望和目的放在了英语和尼日利亚的皮金上。对于数百万的L1土著语言发言人来说，有些不平等表现为无法获得信息，通讯，医疗保健，安全以及对政治和公民生活的参与。为了最大程度地减少排斥和促进社会语言和经济赋权，这项工作探讨了神经机器翻译（NMT）对尼日利亚南部Edoid语言家族的可行性。使用新的JW300公共数据集，我们在该组中培训和评估了四种通用语言的基线翻译模型：èdó，ésán，Urhobo和Isoko。经过培训的模型，代码和数据集已被开源，以推动对Edoid语言技术的未来研究工作。
Many Nigerian languages have relinquished their previous prestige and purpose in modern society to English and Nigerian Pidgin. For the millions of L1 speakers of indigenous languages, there are inequalities that manifest themselves as unequal access to information, communications, health care, security as well as attenuated participation in political and civic life. To minimize exclusion and promote socio-linguistic and economic empowerment, this work explores the feasibility of Neural Machine Translation (NMT) for the Edoid language family of Southern Nigeria. Using the new JW300 public dataset, we trained and evaluated baseline translation models for four widely spoken languages in this group: Èdó, Ésán, Urhobo and Isoko. Trained models, code and datasets have been open-sourced to advance future research efforts on Edoid language technology.
