Neural Machine Translation for Low-resource Languages: A Survey
University of Moratuwa · University of Toronto · +4 more institutions
Abstract
Neural Machine Translation (NMT) has seen tremendous growth in the last ten years since the early 2000s and has already entered a mature phase. While considered the most widely used solution for Machine Translation, its performance on low-resource language pairs remains sub-optimal compared to the high-resource counterparts due to the unavailability of large parallel corpora. Therefore, the implementation of NMT techniques for low-resource language pairs has been receiving the spotlight recently, thus leading to substantial research on this topic. This article presents a detailed survey of research advancements in low-resource language NMT (LRL-NMT) and quantitative analysis to identify the most popular…
Citation impact
- FWCI
- 35.23
- Percentile
- 100%
- References
- 235
Authors
6Topics & keywords
- Computer science
- Machine translation
- Unavailability
- Resource (disambiguation)
- Artificial intelligence
- Natural language processing