We are starting an experiment where we have limited number of sentences in English (probably a few hundred words generating less than a 2000 sentences with max being 5000 sentences) which need to be translated to an experimental language which has a few hundred words (and roughly 2000 sentences with max being 5000). We can guarantee that all the sentences in English will have equivalent translation in the target language and is deterministic i.e. the target language is domain specific and limited.
We are not doing this manually as we have numerous target languages and automating this is better.
(If this works, input languages too can expand beyond English.)
We can across seq2seq which seemed promising but then found OpenNMT which seemed even more promising and are evaluating if openNMT is better. Before we got deeper in openNMT, we wanted to check if openNMT is even fit for purpose given the limited training examples (see below).
Can OpenNMT be used in this scenario ? How many sentences does OpenNMT need to get trained well.