Current Projects

Language Technology for Icelandic 2018-2022

Language Technology for Icelandic 2018-2022

This project is a part of a collaboration effort funded by the Icelandic government to make Icelandic available for use in today’s technological environment. Automatic Speech Recognition, Text-o-Speech and Machine Translation are three of the five core projects defined in the report, Language Technology for Icelandic 2018-2022 (Máltækni fyrir íslensku 2018-2022). Within the collaboration, called Samstarf um íslenska máltækni (SÍM), are nine companies and organizations specialized in linguistics and Natural-Language Processing. Entities within SÍM are Reykjavik University, University of Iceland, Árni Magnússon Institute for Icelandic studies, Blindrafélagið (BIAVI), Ríkisútvarpið (RÚV- National radio), Creditinfo (Media monitoring), Tiro ehf., Grammatek ehf. and Miðeind ehf.
Work on the project started formally the 1st of October 2019 with a 5 year total duration accepted by the Icelandic parliament.

Funding: Language Technology for Icelandic 2018-2022 (Máltækni fyrir íslensku 2018-2022)

Projects:
“Machine Translation (MT) of Icelandic and English”
“Automatic speech recognition (ASR) for Icelandic”
“Text-to-Speech (TTS) for Icelandic speech synthesis”

Timeline: October 2019 – October 2024.


Text-to-Speech (TTS) for Icelandic speech synthesis

Speech data

The Language and Voice Lab is responsible for developing text to speech synthesis for Icelandic in such a manner that it will be possible to produce multiple different voices. LVL will create an environment, and language resources, that will be released to enable players in the market to quickly and simply build synthetic voices for end users. LVL will ensure that the speech synthesis solutions developed can be integrated into software, where e.g. automatic recital or voice answering is needed.

Funding: Language Technology for Icelandic 2018-2022 (Máltækni fyrir íslensku 2018-2022)

Contributors: Atli Thor Sigurgeirsson

Timeline: First iteration: October 2019 – October 2020.


Automatic speech recognition (ASR) for Icelandic

The Language and Voice Lab is responsible for developing automatic speech recognition for Icelandic within the Language Technology for Icelandic project. The aim of developing ASR within the project is to enable people who design and develop voice-based user interfaces to add Icelandic easily. An open environment will be established for the development of speech recognition systems, and recipes for common usage will be made open and accessible.

Funding: Language Technology for Icelandic 2018-2022 (Máltækni fyrir íslensku 2018-2022)

Contributors: Helga Svala Sigurðardóttir, Jón Guðnason, Judy Fong

Timeline: First iteration: October 2019 – October 2020.


Named Entity Recognition – dataset and baselines

Named entities in Icelandic

Named entity recognition (NER) is the task of finding and classifying the named entities (names of people, places, organizations, events, etc.) that appear in text. This is a common preprocessing step before conducting various downstream tasks, such as question answering and machine translation. The aim of this research project is to create the first labelled corpus for Icelandic NER and to use machine learning methods for training a named entity recognizer for Icelandic. This involves labelling all named entities in a text corpus of 1 million tokens (MIM-GOLD), into the following categories: Person, Location, Organization, Micellaneous, Money, Percent, Time, and Date. Using this new data, different machine learning methods (both traditional and deep learning methods) will be tested, and the best performing models selected and combined into a new named entity recognizer for Icelandic. The project is carried out in collaboration with Nasdaq Iceland.

Funding: Strategic Research and Development Programme for Language Technology (Markáætlun í tungu og tækni), Nasdaq Iceland

Contributors: Ásmundur Alma Guðjónsson, Svanhvít Lilja Ingólfsdóttir, Hrafn Loftsson

Timeline: May 2019 – May 2020.


Machine Translation (MT) of Icelandic and English

The goal of machine translation is to translate text or speech between two or more natural languages. In this project the goal is to implement a baseline statistical machine translation system between Icelandic and English and vice versa. The project is a part of the core machine translation project (V3) within the Icelandic National Language Technology Programme, defined in the Language Technology for Icelandic 2018-2022 project plan. We leverage the newly released ParIce corpus, a parallel corpus of 3.5M Icelandic and English translation segments.

Funding: Language Technology for Icelandic 2018-2022 (Máltækni fyrir íslensku 2018-2022)

Contributors: Steinþór Steingrímsson, Haukur Páll Jónsson, Hrafn Loftsson.

Timeline: October 2019 – Summer 2020.


Spoken Dialog System for Automatic Flight Assistant in Icelandic

Spoken Dialog System for Automatic Flight Assistant in Icelandic is a two-semester 60 ECTS Master, project conducted at the Reykjavík University, funded by  Icelandair. The goal is to create a Dialog System that can understand users’ requests, such as to find a flight or to book it.
Dialog System (SDS) is a system that consists of two main components:
Intention Classifier and Slot Tagging.
The goal of this project is to focus on the first part by creating an intention classifier and slot tagging model with sufficient performance, and by doing so create a proof of concept that Icelandic can be already used on an enterprise level.

Funding: Icelandair

Contributors: Egill Anton Hlöðversson, Jón Guðnason

Timeline: Autumn 2019 – Spring  2020


Voice-controlled Information Delivery

The goal of the project is to design a system that enables voice-driven delivery of web content, such as content from news sites, blogs or radio programs. The idea is to have an environment specifically designed for audio interaction and not tied to visual layout of a web page. The user can choose content with voice commands. The content is then presented to the user as audio, e.g. recorded speech or generated speech or a radio episode or podcast. A pure audio interface is useful for situations where hands and eyes are busy, such as when driving, cooking, running, etc., as well as for people with disabilities.

Funding: Tækniþróunarsjóður and menntamálaráðuneytið

iOS App: Broddi

Contributors: Kristján Rúnarsson, Róbert Kjaran, Stefán Jónsson

Timeline: Autumn 2017 – Ongoing


Eyra – speech data acquisition

Eyra is a free and open source project designed to provide tools to gather speech data for languages.

Speech data acquisition is particularly important for under-resourced languages. The data gathering is the most labour-intensive part of developing speech technologies such as automatic speech recognizers and synthesizers.

A screenshot from the Eyra software recording screen where the prompts are read

Eyra aims to make this task cheaper (and better), by  providing a free platform to handle the data acquisition process. Eyra analyzes incoming data and can provide feedback on the quality to attempt to get better quality data.

Designed with flexibility in mind, Eyra is a web app compatible with most browsers, and its offline setting is available by using a laptop as a server. It is open source so you can contribute, use only parts of it, or modify it to suit your needs (e.g. if you want to use pictures instead of prompts).

Currently, Eyra is being used to collect children’s speech data in collaboration with the University of Akureyri.

Funding: Google

Code: https://github.com/Eyra-is/Eyra
Article: SLTU 2016, Building ASR Corpora Using Eyra

Contributors: Matthías Pétursson, Róbert Kjaran, Simon Klüpfel, Judy Fong, Stefán Jónsson

Timeline: Autumn 2016 – Ongoing