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Found 22 papers, 5 papers with code
Pre-training and Evaluating Transformer-based Language Models for Icelandic
We pre-train four types of monolingual ELECTRA and ConvBERT models and compare our results to a previously trained monolingual RoBERTa model and the multilingual mBERT model.
CombAlign: a Tool for Obtaining High-Quality Word Alignments
Being able to generate accurate word alignments is useful for a variety of tasks.
National Language Technology Platform (NLTP): overall view
The work in progress on the CEF Action National Language Technology Platform (NLTP) is presented.
Effective Bitext Extraction From Comparable Corpora Using a Combination of Three Different Approaches
Parallel sentences extracted from comparable corpora can be useful to supplement parallel corpora when training machine translation (MT) systems.
Compiling a Highly Accurate Bilingual Lexicon by Combining Different Approaches
By combining the most promising approaches and data sets, using confidence scores calculated from the data and the results of manually evaluating samples from our manual evaluation as indicators, we are able to induce lists of translations with a very high acceptance rate.
National Language Technology Platform for Public Administration
This article presents the work in progress on the collaborative project of several European countries to develop National Language Technology Platform (NLTP).
Towards High Accuracy Named Entity Recognition for Icelandic
We report on work in progress which consists of annotating an Icelandic corpus for named entities (NEs) and using it for training a named entity recognizer based on a Bidirectional Long Short-Term Memory model.
SentAlign: Accurate and Scalable Sentence Alignment
We present SentAlign, an accurate sentence alignment tool designed to handle very large parallel document pairs.
Building an Icelandic Entity Linking Corpus
We describe our approach of using a multilingual entity linking model (mGENRE) in combination with Wikipedia API Search (WAPIS) to label our data and compare it to an approach using WAPIS only.
Semi-self-supervised Automated ICD Coding
Clinical Text Notes (CTNs) contain physicians' reasoning process, written in an unstructured free text format, as they examine and interview patients.
Effectively Aligning and Filtering Parallel Corpora under Sparse Data Conditions
When rich morphology exacerbates the data sparsity problem, it is imperative to have accurate alignment and filtering methods that can help make the most of what is available by maximising the number of correctly translated segments in a corpus and minimising noise by removing incorrect translations and segments containing extraneous data.
Kvistur 2.0: a BiLSTM Compound Splitter for Icelandic
In this paper, we present a character-based BiLSTM model for splitting Icelandic compound words, and show how varying amounts of training data affects the performance of the model.
Language Technology Programme for Icelandic 2019-2023
In this paper, we describe a new national language technology programme for Icelandic.
A Wide-Coverage Context-Free Grammar for Icelandic and an Accompanying Parsing System
Our parsing system is able to parse about 90{\%} of all sentences in articles published on the main Icelandic news websites.
Nefnir: A high accuracy lemmatizer for Icelandic
Lemmatization, finding the basic morphological form of a word in a corpus, is an important step in many natural language processing tasks when working with morphologically rich languages.
Augmenting a BiLSTM tagger with a Morphological Lexicon and a Lexical Category Identification Step
Previous work on using BiLSTM models for PoS tagging has primarily focused on small tagsets.
Rapid Deployment of Phrase Structure Parsing for Related Languages: A Case Study of Insular Scandinavian
This paper presents ongoing work that aims to improve machine parsing of Faroese using a combination of Faroese and Icelandic training data.
Correcting Errors in a New Gold Standard for Tagging Icelandic Text
We describe manual correction and a method for semi-automatic error detection and correction.
