According to Cambra and Zafeiridou, low-resource languages don’t necessarily mean smaller models. In fact, they will need more complex architectures in order to perform up to par with languages for which there is more data available.
Working with low resource languages is a research concern that has become a lot more significant lately, especially with the recent news about Meta’s pioneering open-source No Language Left Behind Project (NLLB).
Learn more about the ramifications of the NLLB project on low resource languages in our article: No Language Left Behind: Meta’s Massive Multilingual Machine Translation Ambition Pays It Forward
The first day capped off with a poster session that asked bosnia and herzegovina mobile database the question: “What if we had the perfect translation system?” One major highlight of this panel was the discussion on the role of the translator in such a scenario.
The translator’s skillset is a crucial factor in making the best use of such a machine translation system, going beyond translation and even beyond post-editing to take on a more evolved role.
Another highlight of this discussion was the problem of authorship and copyright. Raw MT output is not protected by copyright, as it does not fulfill the criteria required to define the work done on the text as “creative”. Post-editing complicates things slightly, as it raises the question of whether the human intervention might result in the creation of an “original” work.