Icelandic Parallel Abstracts Corpus
This addresses a data scarcity problem for NLP researchers working on Icelandic language tasks, but it is incremental as it applies an existing method to new data.
The authors tackled the lack of Icelandic-English parallel data by creating the Icelandic Parallel Abstracts Corpus (IPAC), resulting in a corpus of 64k sentence pairs from over 6 thousand parallel abstracts.
We present a new Icelandic-English parallel corpus, the Icelandic Parallel Abstracts Corpus (IPAC), composed of abstracts from student theses and dissertations. The texts were collected from the Skemman repository which keeps records of all theses, dissertations and final projects from students at Icelandic universities. The corpus was aligned based on sentence-level BLEU scores, in both translation directions, from NMT models using Bleualign. The result is a corpus of 64k sentence pairs from over 6 thousand parallel abstracts.