Workflows for kickstarting RBMT in virtually No-Resource Situation

LLM-Assisted Rule Based Machine Translation for Low/No-Resource Languages

We propose a new paradigm for machine translation that is particularly useful for no-resource languages (those without any publicly available bilingual or monolingual corpora): LLM-RBMT (LLM-Assisted Rule Based Machine T…

Boosting Neural Machine Translation from Finnish to Northern Sámi with Rule-Based Backtranslation

We consider a low-resource translation task from Finnish into Northern Sámi. Collecting all available parallel data between the languages, we obtain around 30,000 sentence pairs. However, there exists a significantly lar…

RBMT as an alternative to SMT for under-resourced languages

Kickstarting Deep Reinforcement Learning

We present a method for using previously-trained 'teacher' agents to kickstart the training of a new 'student' agent. To this end, we leverage ideas from policy distillation and population based training. Our method plac…

A case study on English-Malayalam Machine Translation

In this paper we present our work on a case study on Statistical Machine Translation (SMT) and Rule based machine translation (RBMT) for translation from English to Malayalam and Malayalam to English. One of the motivati…