  Unlike English, morphologically rich languages can reveal characteristics of
speakers or their conversational partners, such as gender and number, via
pronouns, morphological endings of words and syntax. When translating from
English to such languages, a machine translation model needs to opt for a
certain interpretation of textual context, which may lead to serious
translation errors if extra-textual information is unavailable. We investigate
this challenge in the English-to-Polish language direction. We focus on the
underresearched problem of utilising external metadata in automatic translation
of TV dialogue, proposing a case study where a wide range of approaches for
controlling attributes in translation is employed in a multi-attribute
scenario. The best model achieves an improvement of +5.81 chrF++/+6.03 BLEU,
with other models achieving competitive performance. We additionally contribute
a novel attribute-annotated dataset of Polish TV dialogue and a morphological
analysis script used to evaluate attribute control in models.
