Evaluation of Abstractive Summarisation Models with Machine Translation in Deliberative Processes
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.
- Pub Date:
- October 2021
- Computer Science - Computation and Language;
- Computer Science - Computers and Society;
- Computer Science - Machine Learning
- 8 pages, presented in EMNLP 2021 - New Frontiers in Summarization Workshop