  We present work on summarising deliberative processes for non-English
languages. Unlike commonly studied datasets, such as news articles, this
deliberation dataset reflects difficulties of combining multiple narratives,
mostly of poor grammatical quality, in a single text. We report an extensive
evaluation of a wide range of abstractive summarisation models in combination
with an off-the-shelf machine translation model. Texts are translated into
English, summarised, and translated back to the original language. We obtain
promising results regarding the fluency, consistency and relevance of the
summaries produced. Our approach is easy to implement for many languages for
production purposes by simply changing the translation model.
