Language Technology Programme for Icelandic 2019-2023

In this paper, we describe a new national language technology programme for Icelandic. The programme, which spans a period of five years, aims at making Icelandic usable in communication and interactions in the digital world, by developing accessible, open-source language resources and software. The research and development work within the programme is carried out by a consortium of universities, institutions, and private companies, with a strong emphasis on cooperation between academia and industries. Five core projects will be the main content of the programme: language resources, speech recognition, speech synthesis, machine translation, and spell and grammar checking. We also describe other national language technology programmes and give an overview over the history of language technology in Iceland.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/04/2020

Cross-Lingual Machine Speech Chain for Javanese, Sundanese, Balinese, and Bataks Speech Recognition and Synthesis

Even though over seven hundred ethnic languages are spoken in Indonesia,...
research
10/27/2015

Standards for language resources in ISO -- Looking back at 13 fruitful years

This paper provides an overview of the various projects carried out with...
research
04/06/2021

AI4D – African Language Program

Advances in speech and language technologies enable tools such as voice-...
research
10/14/2020

Google Crowdsourced Speech Corpora and Related Open-Source Resources for Low-Resource Languages and Dialects: An Overview

This paper presents an overview of a program designed to address the gro...
research
02/28/2023

The 2022 NIST Language Recognition Evaluation

In 2022, the U.S. National Institute of Standards and Technology (NIST) ...
research
05/06/2022

Hearing voices at the National Library – a speech corpus and acoustic model for the Swedish language

This paper explains our work in developing new acoustic models for autom...
research
02/25/2022

Language technology practitioners as language managers: arbitrating data bias and predictive bias in ASR

Despite the fact that variation is a fundamental characteristic of natur...

Please sign up or login with your details

Forgot password? Click here to reset