Abstract
Users of machine translation systems may desire to obtain multiple candidates translated
in different ways. In this work, we attempt
to obtain diverse translations by using sentence codes to condition the sentence generation. We describe two methods to extract
the codes, either with or without the help of
syntax information. For diverse generation,
we sample multiple candidates, each of which
conditioned on a unique code. Experiments
show that the sampled translations have much
higher diversity scores when using reasonable
sentence codes, where the translation quality
is still on par with the baselines even under
strong constraint imposed by the codes. In
qualitative analysis, we show that our method
is able to generate paraphrase translations with
drastically different structures. The proposed
approach can be easily adopted to existing
translation systems as no modification to the
model is required