Building a dual dataset of text- and image-grounded conversations and summarisation in Gàidhlig (Scottish Gaelic)

Abstract

• Gàidhlig (Scottish Gaelic; gd) is spoken by about 57k people in Scotland,1 but remains an under-resourced language with respect to natural language processing in general and natural language generation (NLG) in particular. To address this gap, we developed the first datasets for Scottish Gaelic NLG, collecting both conversational and summarisation data in a single setting. Our task setup involves dialogues between a pair of proficient speakers discussing museum exhibits, grounding the conversation in images and texts. Then, each interlocutor summarises the dialogue resulting in a secondary dialogue summarisation dataset. This paper presents the dialogue and summarisation corpora, as well as the software used for data collection. The dialogue dataset consists of 43 conversations (13.7k words) and 61 summaries (2.0k words).2