Helping Our Own: Text Massaging for Computational Linguistics as a New Shared Task

In this paper, we propose a new shared task called HOO: Helping Our Own. The aim is to use tools and techniques developed in computational linguistics to help people writing about computational linguistics. We describe a text-to-text generation scenario that poses challenging research questions, and delivers practical outcomes that are useful in the first case to our own community and potentially much more widely. Two specific factors make us optimistic that this task will generate useful outcomes: one is the availability of the ACL Anthology, a large corpus of the target text type; the other is that CL researchers who are non-native speakers of English will be motivated to use prototype systems, providing informed and precise feedback in large quantity. We lay out our plans in detail and invite comment and critique with the aim of improving the nature of the planned exercise.

• Type: Journal
• Year: 2010
• Where: INLG
• Authors: Robert Dale, Adam Kilgarriff
• Keywords: Computational Linguistics, INLG 2010, Natural Language Processing, Target Text Type, Text-to-text Generation Scenario