A Collaborative Platform to Collect Data for Developing Machine Translation Systems

The emergence of neural machine translation techniques has opened up a new era for developing translation systems. However, it requires a very large amount of parallel corpus, which is scarce for many under-resourced languages, e.g., Bangla. In order to develop a corpus, currently, there is a lack of publicly available collaborative system. In this paper, we report an online collaborative system for the development of the parallel corpus. The system is developed for supporting any language, however, we only evaluated for developing Bangla–English parallel corpus. In a task completion evaluation experiment, the system outperforms the widely used offline system, i.e., OmegaT.