Þórunn Arnardóttir


Developing a Spell and Grammar Checker for Icelandic using an Error Corpus
Hulda Óladóttir | Þórunn Arnardóttir | Anton Ingason | Vilhjálmur Þorsteinsson
Proceedings of the Thirteenth Language Resources and Evaluation Conference

A lack of datasets for spelling and grammatical error correction in Icelandic, along with language-specific issues, has caused a dearth of spell and grammar checking systems for the language. We present the first open-source spell and grammar checking tool for Icelandic, using an error corpus at all stages. This error corpus was in part created to aid in the development of the tool. The system is built with a rule-based tool stack comprising a tokenizer, a morphological tagger, and a parser. For token-level error annotation, tokenization rules, word lists, and a trigram model are used in error detection and correction. For sentence-level error annotation, we use specific error grammar rules in the parser as well as regex-like patterns to search syntax trees. The error corpus gives valuable insight into the errors typically made when Icelandic text is written, and guided each development phase in a test-driven manner. We assess the system’s performance with both automatic and human evaluation, using the test set in the error corpus as a reference in the automatic evaluation. The data in the error corpus development set proved useful in various ways for error detection and correction.

Error Corpora for Different Informant Groups:Annotating and Analyzing Texts from L2 Speakers, People with Dyslexia and Children
Þórunn Arnardóttir | Isidora Glisic | Annika Simonsen | Lilja Stefánsdóttir | Anton Ingason
Proceedings of the 19th International Conference on Natural Language Processing (ICON)

Error corpora are useful for many tasks, in particular for developing spell and grammar checking software and teaching material and tools. We present and compare three specialized Icelandic error corpora; the Icelandic L2 Error Corpus, the Icelandic Dyslexia Error Corpus, and the Icelandic Child Language Error Corpus. Each corpus contains texts written by speakers of a particular group; L2 speakers of Icelandic, people with dyslexia, and children aged 10 to 15. The corpora shed light on errors made by these groups and their frequencies, and all errors are manually labeled according to an annotation scheme. The corpora vary in size, consisting of errors ranging from 7,817 to 24,948, and are published under a CC BY 4.0 license. In this paper, we describe the corpora and their annotation scheme, and draw comparisons between their errors and their frequencies.


A Universal Dependencies Conversion Pipeline for a Penn-format Constituency Treebank
Þórunn Arnardóttir | Hinrik Hafsteinsson | Einar Freyr Sigurðsson | Kristín Bjarnadóttir | Anton Karl Ingason | Hildur Jónsdóttir | Steinþór Steingrímsson
Proceedings of the Fourth Workshop on Universal Dependencies (UDW 2020)

The topic of this paper is a rule-based pipeline for converting constituency treebanks based on the Penn Treebank format to Universal Dependencies (UD). We describe an Icelandic constituency treebank, its annotation scheme and the UD scheme. The conversion is discussed, the methods used to deliver a fully automated UD corpus and complications involved. To show its applicability to corpora in different languages, we extend the pipeline and convert a Faroese constituency treebank to a UD corpus. The result is an open-source conversion tool, published under an Apache 2.0 license, applicable to a Penn-style treebank for conversion to a UD corpus, along with the two new UD corpora.