Cross-Lingual QA as a Stepping Stone for Monolingual Open QA in Icelandic

Abstract

It can be challenging to build effective open question answering (open QA) systems for languages other than English, mainly due to a lack of labeled data for training. We present a data efficient method to bootstrap such a system for languages other than English. Our approach requires only limited QA resources in the given language, along with machine-translated data, and at least a bilingual language model. To evaluate our approach, we build such a system for the Icelandic language and evaluate performance over trivia style datasets. The corpora used for training are English in origin but machine translated into Icelandic. We train a bilingual Icelandic/English language model to embed English context and Icelandic questions following methodology introduced with DensePhrases (Lee et al., 2021). The resulting system is an open domain cross-lingual QA system between Icelandic and English. Finally, the system is adapted for Icelandic only open QA, demonstrating how it is possible to efficiently create an open QA system with limited access to curated datasets in the language of interest.

Brief communication: Small-scale geohazards cause significant and highly variable impacts on emotions

“…To label the other tweets automatically an already adapted language model was fine-tuned on the manually annotated data for use in labeling as follows: The data was split randomly into a train and validation set of 493 and 121 tweets respectively. An pre-trained Icelandic-English language model (Snaebjarnarson and Einarsson, 2022)…”