heilsugaeslan

Building language technology applications to help nations, industry, medicine, language learning, and users.

Sjá íslenska þýðingu neðar

We have received five grants. We are also welcoming a new RU professor to LVL, Hannes Högni Vilhjálmsson. For these grants we are hiring specialists in artificial intelligence, language technology and software development. The deadline for the job applications are March 15th, 2021. Three grants are from the Icelandic Centre for Research and two are from the European CEF-Telecom program. The grants were for the following projects:

Microservices at your service: bridging the gap between NLP research and industry

This project aims to increase inclusiveness and accessibility for the EU languages by making natural language processing (NLP) tools freely and openly available on the European Language Grid (ELG) platform. The project will make the NLP tools more accessible to a larger audience of software developers through:

  • identifying relevant and interesting NLP tools. The tools will be identified via a bottom-up search on the software platforms, as well as by contacting the research institutions;
  • conducting a survey and collecting standard or available test data sets for NLP tasks;
  • testing the set of collected tools on the existing test data and selecting them based on the metrics performance and language coverage;
  • dockerising the tools and expose an industry standard API to the service;
  • sharing the docker images via the ELG platform.

The project targets the following languages: Finnish, Swedish, Norwegian, Spanish, Portuguese, Icelandic, Faroese, Lithuanian, Latvian and Estonian.

This project will be developed in collaboration with the University of Tartu (Estonia) and Gradient (Spain).

National Language Technology Platform (NLTP)

In this project, the most advanced language technology (LT) tools and solutions will be united in a novel, artificial intelligence driven National Language Technology Platform (NLTP). By tightly integrating mature, state-of-the-art LT technologies and services developed in CEF AT and other European and national programmes, the NLTP will provide public administrations, SMEs and general public with an efficient way to ensure multilingual access to online services, websites, documents and information removing the language barriers, increasing accessibility and fostering cross-border services.

The translation and speech processing services available in the platform will give public administration entities, their employees, SMEs and the public convenient and secure access to high quality tools with which to translate and make accessible a wide array of content, including confidential documents, across all the languages of the Digital Single Market and finally enable the vision of language parity and the full multilingualism enshrined in the European Charter of Fundamental Rights in an efficient, cost effective, and equitable manner.

This project is in collaboration with Culture Information Systems Centre (Latvia), Malta Information Technology Agency, Office of the State Advocate (Malta), University of Malta, University of Tartu (Estonia), Central State Office for the Development of Digital Society (Croatia), and University of Zagreb (Croatia).

Spoken Dialogue Framework for Icelandic

The spoken dialogue framework enables users to communicate with computers and other devices with their voice in Icelandic. The goal of this project is to develop and provide an open development framework for Icelandic spoken dialogue. The framework will feature automatic speech recognition (ASR), language understanding questions, text-to-speech synthesis (TTS), as well as several other language modules. Sseveral of these modules are already in development as part of the five year Language Technology Programme for Icelandic while others will be new developments or areas for end users. This project will be developed and tested in collaboration with industry partners (Grammatek ehf and Tiro ehf) as well as the open sector.

Using Machine Learning Models for Clinical Diagnoses

The goal is to examine the feasibility of using automatic models for clinical analyses. The project consists of two sub-goals. The first sub-goal is to develop a model based on deep neural networks which will use data from the icelandic healthcare system. The second sub-goal is to develop a prediction model for clinical diagnoses. The dataset will come from the capital region’s healthcare clinics. A portion of the dataset will be handmarked by clinical experts. This project will be developed jointly by LVL and Heilsugæsla, the health clinics.

Computer-Assisted Pronunciation Training in Icelandic

Language technology can be used to make teaching easier and more fun. It is important for small languages like Icelandic to get more users and an important step in getting more users is language learning and teaching. Computer-assisted pronunciation training (CAPT) makes it easier to teach more students simultaneously and automatically. This training will be integrated with the Icelandic Online system used in the Icelandic as a second language program at the University of Iceland. This project will be developed and tested in collaboration with our partners at Tiro ehf, the Arni Magnusson Institute, and the University of Iceland.

Íslenska

Að byggja upp tungumálatækniforrit til að hjálpa þjóðum, iðnaði, læknisfræði, tungumálanámi og notendum

Um er að ræða tvo styrki úr evrópsku “CEF-Telecom” áætluninni og þrjá styrki úr “Markáætlun í tungu og tækni”. Fyrir þessa styrki erum við að ráða sérfræðinga í gervigreind, máltækni og hugbunaðargerð. Skilafrestur umsókna um starf er til 15. mars 2021. Við bjóðum einnig Hannes Högni Vilhjálmsson prófessor við Háskólann í Reykjavík velkominn til LVL. Heiti verkefnanna sem um ræðir eru:

Örþjónustur til þjónustu: hvernig á að brúa bilið á milli NLP rannsókna og atvinnulífs

Þetta verkefni miðar að því að auka aðgengi að tungumálum töluðum innan ESB með því að gera þau tæki og tól sem þarf til málvinnslu (NLP) opin og aðgengileg á vettvangi European Language Grid (ELG). Verkefnið mun gera NLP tól aðgengilegri fyrir stærri hóp forritara með því að:

  • Greina viðeigandi og áhugaverð NLP tól. Tólin verða greind með neðansækinni leit á ýmsum hugbúnaðarverkvöngum semog með því að hafa samband við rannsóknarstofnanir.
  • Framkvæma könnun og söfnun á stöðluðum eða tiltækum prófunargögnum fyrir NLP verkefni.
  • Prófa tólin á prófunargögnunum og velja þau sem koma best út úr prófunum miðað við tiltekna matsþætti.
  • Docker-væða tólin og útbúa stöðluð forrritaskil fyrir viðkomandi þjónustur.
  • Deila docker-myndum í gegnum ELG-verkvanginn.

Verkefnið beinist að eftirfarandi tungumálum: finnsku, sænsku, norsku, spænsku, portúgölsku, íslensku, færeysku, litháísku, lettnesku og eistnesku.

Þetta verkefni verður þróað í samvinnu við fyrirtækið LingSoft í Finnlandi, Háskólann í Tartu (Eistlandi) og rannsóknarstofnunina Gradient (Spáni).

National Language Technology Platform (NLTP)

Í þessu verkefni verða hágæða máltæknitól og lausnir (LT) samþættuð í gervigreindarstýrðum „National Language Technology Platform“ (NLTP). Með því að samþætta „state-of-the-art“ LT lausnir og þjónustur sem þróaðar hafa verið í CEF AT, og öðrum evrópskum og innlendum áætlunum, mun NLTP veita opinberum aðilum, litlum og meðalstórum fyrirtækjum og almenningi skilvirka leið til að tryggja fjöltyngdan aðgang að þjónustu á netinu, vefsíðum, skjölum og upplýsingum. Þannig er hægt að fjarlægja tungumálahindranir, auka aðgengi og efla þjónustu yfir landamæri.

Þýðingar- og talvinnsluþjónustan sem verður aðgengileg í NLTP mun veita opinberum aðilum, starfsmönnum þeirra, litlum og meðalstórum fyrirtækjum og almenningi auðveldan og öruggan aðgang að hágæða lausnum til að þýða og gera aðgengilegt fjölbreytt úrval af efni á öllum tungumálum hins stafræna sameiginlega markaðar (Digital Single Market). Þannig getur sú sýn um tungumálafjölbreytileika og fjöltyngi sem fram kemur í sáttmála Evrópusambandsins um grundvallarréttindi orðið að veruleika á skilvirkan, hagkvæman og sanngjarnan máta.

Þetta verkefni er unnið í samvinnu við Tilde (Latvia), Culture Information Systems Centre (Latvia), Malta Information Technology Agency, Office of the State Advocate (Malta), University of Malta, University of Tartu (Estonia), Central State Office for the Development of Digital Society (Croatia) og University of Zagreb (Croatia).

Þróunarumgjörð fyrir íslenskt samræðukerfi

Samræðukerfi gera notendum kleift að eiga í samskiptum við tölvur og tæki með tali. Markmið þessa verkefnis er að þróa og gefa út opna þróunarumgjörð fyrir íslenskt samræðukerfi. Einnig verða til frumgerðir hugbúnaðar til sjálfvirkrar símsvörunar hjá einkafyrirtæki og til upplýsingagjafar á opinberri heimasíðum, sem byggja á þróunarumgjörðinni. 

Helstu þættir samræðukerfis eru: 1) talgreining, sem umbreytir tali notanda í texta; 2) málskilningur, sem greinir spurningar notanda með það að markmiði að “skilja” markmið hans; 3) samræðustjórnun, sem stýrir viðbrögðum kerfisins, til dæmis hvaða svar á að gefa eða hvaða aðgerð á að framkvæma, og sem jafnframt tengist gagnagrunnum, þjónustum og/eða öðrum uppsprettum upplýsinga; 4) málmyndun, sem myndar svar til notanda á textaformi; og 5) talgerving, sem umbreytir texta í talskilaboð til notanda. 

Þessi undirkerfi verða þróuð eða aðlöguð fyrir íslensku innan verkefnisins. Mörg þeirra eru nú þegar í þróun innan Máltækniáætlunar fyrir íslensku og mun verkefnið því geta nýtt þær afurðir ásamt því að leggja til frekari þróun á ýmsum sviðum. 

Tvær frumgerðir hugbúnaðar fyrir endanotendur verða þróaðar og prófaðar í samvinnu við samstarfsaðila úr atvinnulífinu og opinbera geiranum. Verkefnið tengist því sterklega bæði rannsóknum og hagnýtingu máltækni fyrir íslensku.

Notkun vélnámslíkana fyrir klínískar greiningar

Markmiðið með þessu verkefni er að skoða hagkvæmni þess að nota vélnámslíkön fyrir klínískar greiningar Verkefnið samanstendur af tveimur undirmarkmiðum. Í fyrsta lagi að nota djúptauganet til að þróa útdráttarlíkan sem dregur út einkenni úr íslenskum sjúkraskýrslum. Í öðru lagi að nota einkennin til að þjálfa greiningarlikan sem spáir fyrir um klínískar greiningar.

Gagnasafnið okkar samanstendur af nótum úr sjúkraskrám sjúklinga frá Heilsugæslu höfuðborgarsvæðisins. Hluti gagnasafnsins verður handmerktur þannig að sérhvert klínískt einkenni í nótu er merkt, ásamt því textabili í nótunni sem vísar í viðkomandi einkenni.

Djúptauganetin (bæði biLSTM og BERT-líkön) verða þjálfuð með því að nota handmerktu nóturnar og spurningu sem inntak, með það að markmiði að besta fyrir því textabili sem inniheldur svarið við spurningunni. Þannig lærir útdráttarlíkanið að draga út klínísk einkenni sem tengjast þeirri spurningu sem sett er fram í samhengi við viðkomandi nótu. 

Fyrir þróun á greiningarlíkaninu, sem tekur einkenni frá útdráttarlíkaninu sem inntak og skilar klínískri greiningu sem úttaki, munum við gera tilraunir með ýmiss konar flokkunaraðferðir, eins og “”Logistic Regression””, “”Decision Trees”” og “”Random Forest””. Greiningarfærni líkansins verður að lokum borin saman við greiningarfærni lækna á heilsugæslu.”

Tölvustudd frambuðarþjálfun á íslensku

Máltækni má nota til að gera tungumálakennslu auðvaldari og skemmtilegri. Það er mjög mikilvægt að geta fjölgað málnotendum minni tungumála eins og íslensku og skilvirk tungumálakennsla er góð leið til að ná slíku markmiði. Tölvustudd framburðarþjálfun (e. CAPT) gerir kennslu margra nemanda auðvaldari og gerir tölvustudda tungumálakennslu skilvirkari og auðveldari. 

Þetta verkefni miðar að því að smíða kerfi fyrir tölvustudda framburðarkennslu fyrir íslensku. Framburðar- og ítónunareiningar gera kerfinu kleift að hlusta á og meta framburð nemenda og gefa þeim nothæfa endurgjöf við nám sitt. Verkefnið inniheldur einnig vinnu við þróun á framburðarmati með mörgum markmiðum og kvikri einkunnargjöf þar sem gæði kerfisins er hámarkað og virkni útvíkkað. Framburðarkerfið verður samþætt og prófað sem hluti af Icelandic Online kerfinu sem er þegar í notkun við tungumálakennslu á íslensku sem annað máls.   

TTS, Language Technology, Kvistur, and Samrómur papers published but no conferences to attend

Sjá íslenska þýðingu neðar

This is a positive but somewhat sad week for LVL. Many LVL members were going to go to Marseille, France this week to attend Language Resources & Evaluation Conference (LREC) 2020 and the joint Spoken Language Technologies for Under-Resourced Languages and Collaboration and Computing for Under-Resourced Languages (SLTU-CCURL) 2020 Workshop. Once there they were going to present their many papers, providing an in-depth look into our TTS, data collection, compound splitting, and general language technology research in recent months. However, due to COVID-19 these conferences were both cancelled. Luckily the organizers have still decided to publish the proceedings this month. The joint SLTU proceedings were published May 8th on the SLTU-CCURL 2020 website at Workshop Proceedings (our paper is on page 316). Head over to the SLTU 2020 website if you want to read more SLTU-CCURL papers. We’re still waiting for the LREC proceedings to be published. But our papers can now be found as pdfs below and on our publications page.

Our TTS paper was accepted at SLTU-CCURL 2020:



Title: Manual Speech Synthesis Data Acquisition – From Script Design to Recording Speech
Authors: Atli Þor Sigurgeirsson, Gunnar Thor Örnólfsson, Jon Gudnason
Summary: In this paper we present the work of collecting a large amount of high quality speech synthesis data for Icelandic. A script design strategy is proposed and three scripts have been generated to maximize diphone coverage, varying in length. The largest reading script contains 14,400 prompts and includes 81% of all Icelandic diphones at least twenty times. As of writing, 58.7 hours of high quality speech data has been collected.
PDF

Our Samrómur, Kvistur, and Language Technology programme papers were accepted at LREC 2020:

The cover of the proposal sent to the Icelandic parliament

Title: Language Technology Programme for Icelandic 2019-2023
Authors: Anna Nikulásdóttir, Jón Guðnason, Anton Karl Ingason, Hrafn Loftsson, Eiríkur Rögnvaldsson, Einar Freyr Sigurðsson and Steinþór Steingrímsson
Summary: In this paper, we describe a national language technology programme for Icelandic. The programme aims at making Icelandic usable in communication and interactions in the digital world, by developing accessible, opensource language resources and software. The research and development work within the programme is carried out by SÍM, 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.
PDF

A representation of the model with one BiLSTM layer, showing where the compound word raforku ‘electric energy’ is split in two.

Title: Kvistur: a BiLSTM Compound Splitter for Icelandic
Authors: Jón Daðason, David Mollberg and Hrafn Loftsson
Summary: In this paper, we present a character-based BiLSTM model for splitting Icelandic compound words, and show how quantity of training data affects model performance. Compounding is highly productive in Icelandic, and new compounds are constantly being created. This results in a large number of out-of-vocabulary (OOV) words, negatively impacting the performance of many NLP tools. Our model is trained on a dataset of 2.9 million unique word forms and their constituent structures from the Database of Icelandic Morphology. The model learns to split compound words into two and can be used to derive a word form’s constituent structure. Knowing the constituent structure of a word form makes it possible to generate the optimal split for a given task. The model outperforms other previously published methods when evaluated on a corpus of manually split word forms. This method has been integrated into Kvistur, an Icelandic compound word analyzer.
PDF

The cumulative count of votes and utterances. Each utterance can have more than one vote as it needs two positive votes to be considered valid and two negative votes to be considered invalid.

Title: Samrómur: Crowd-sourcing Data Collection for Icelandic Speech Recognition
Authors: David Erik Mollberg, Ólafur Helgi Jónsson, Sunneva Þorsteinsdóttir, Steinþór Steingrímsson, Eydís Huld Magnúsdóttir and Jon Gudnason
Summary: This contribution describes an ongoing speech data collection, using Samrómur which is built upon Mozilla’s Common Voice. The goal is to build a large-scale speech corpus for Automatic Speech Recognition (ASR) for Icelandic. Upon completion, Samrómur will be the largest open speech corpus for Icelandic. The paper discusses the methods used for crowd-sourcing and illustrate the importance of marketing and good media coverage for a crowd-sourced dataset. Preliminary results exceed our
expectations. The paper also reports on the process of validating recordings.
PDF

Our SÍM colleagues also had two papers at LREC 2020: “Facilitating Corpus Usage: Making Icelandic Corpora More Accessible for Researchers and Language Users” and “Parallel Universal Dependencies”. Congratulations!

While it is sad that our LVL members cannot meet with fellow researchers and visit the great city of Marseille, they still look forward to connecting with researchers online through your comments on their papers and links to your related papers.

Þessa vikuna hefði átt að halda Language Resources & Evaluation (LREC) ráðstefnuna í Frakklandi, sem og Spoken Language Technologies for Under-resourced Languages vinnustofuna en báðum þessum viðburðum var aflýst vegna COVID-19.  Margir starfsmenn LVL ætluðu sér að sækja þessa viðburði og kynna þar 4 greinar og veita innsýn í þær máltæknirannsóknir sem hafa farið fram hérna síðustu mánuði. Hérna má lesa nánar um þetta og nálgast greinarnar. (Athugið að greinarnar eru aðeins aðgengilegar á ensku).

A large milestone in Named Entity Recognition for Icelandic!

Progress in NER celebrated with a suitable cake.

Last Tuesday Svanhvít and Ásmundur completed the first stage in Named Entity Recognition project for Icelandic. They finished the daunting task of labeling 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.

To assist with the task, they first preprocessed the corpus using regular expressions to catch some cases and then verified and completed the labeling using the brat rapid annotation tool. Their next task will be to create a few baseline NER tagging systems using the labelled dataset.

The dataset will be publicly available this spring.

First milestone in the Language Technology for Icelandic project

The LVL team celebrating the first milestone in the Language Technology for Icelandic project. Ólafur Helgi Jónsson, Sunneva Þorsteinsdóttir and Steinþór Steingrímsson are missing from the picture.

Last week we celebrated achieving the first milestone in the Language Technology for Icelandic project with a cake!

After a lot of hard work the past few months we achieved the first milestone in Automatic Speech Recognition (ASR), Text-to-Speech (TTS) and Machine Translation (MT).

In ASR, the focus has mostly been on data creating and gathering. 55,000 utterances have been collected (donated by adults) via the crowd-sourcing platform samromur.is (based on Common Voice) with plans to reach 100.000 utterances for the next milestone. The process is being extended to include younger voices in collaboration with schools and authorities. Today we started working with Öldutúnsskóli in Hafnarfjörður. The goal is to reach 80.000 young voice utterances for the next mileston. Additionally, data has been gathered from RÚV (audio, video and subtitles) and CreditInfo (transcriptions). Along with data gathering, the team is also developing tools to post-process Icelandic ASR text for better readability.

In TTS, we successfully created a voice recording client (LOBE) and three reading scripts in order to collect high quality speech and corresponding text data. The reading scripts were created from Risamálheild and seek to maximize diphone coverage. So far 20 hours have been collected from two speakers, male and female. The aim is to finish collecting 20 hours from each speaker early this year. From the collected data two TTS prototypes have been created in Ossian, which extends the Merlin back-end. The current prototypes are quite naive but we have integrated a grapheme-to-phoneme model for the Icelandic language into the prototypes.

In MT, we successfully created a phrase-based statistical machine translation system using the open source tool Moses. Our collaborators at Miðeind created neural machine translation systems based on BiLSTMs and Transformers. The models were trained on the newly available English-Icelandic parallel corpus, ParIce. The systems were then evaluated w.r.t. training time, throughput and BLEU score. The code and 
systems are freely available but are still under development for milestone two. In milestone two we will continue to develop the systems further and adjust them to specific needs of the Icelandic language.

Donate your voice to bring Icelandic and technology together!

Hello everyone!

We are collecting audio clips to create a new, more robust Icelandic dataset. We plan to use them for automatic speech recognition and text-to-speech applications. This could lead to many applications that you can use in your everyday life, like an Icelandic voice assistant, screenreaders, and searchable audio and video content. The dataset will soon be available directly on the Samromur website for users and developers alike to download and use to creating exciting new technology. But to do this, we need your voices, Icelandic speakers.

You can get started by going to Samromur.is  and choosing Tala. You only need to donate 5 recordings per session, but more is always welcome. If you want to do more, you can also evaluate clips made by other users with Hlusta.

Samromur

 

We are also organizing data gathering competitions within companies. So, please contact us if you and your company would be interested in holding a competition.

This is a joint effort with Deloitte and Almannaromur. If you want to learn more about this project, visit the Um Verkefnið tab on the Samromur site.

Conference – Er íslenskan góður „bisness“?

Tomorrow, 16th of October 2019, there will be a conference on Icelandic language technology. The conference will take place at Veröld – hús Vigdísar and starts at 8:00.

A number of people affiliated (past and present) with the LVL will be giving talks there such as:

  • David Erik Mollberg, Ólafur Helgi Jónsson, Viktor Sveinsson Sunneva Þorsteinssdóttir – students at HÍ and RU will launch an open speech data collection initivate for Icelandic.
  • Anna Björk Nikulásdóttir – project manager at SÍM (Samstarf um íslenska máltækni – Collaboration on Icelandic Language Technology) and CEO of Grammatek will talk about tools in language technology.
  • Hrafn Loftsson – docent at the School of Computer Science in RU will talk about automatic text summarization for Icelandic.

The conference focuses on the importance of Icelandic language technology for academy and industry and is open for anyone to attend.

For more details on the conference and speaker list, see the facebook event (Icelandic)

Tune in this weekend as Rás 1 interviews ASR expert Inga Rún and Althingi editor, Steinunn about the Icelandic Parliament’s automated transcription system.

September 2019 signals the end of the LVL automatic speech recognition, ASR, project with Althingi, the Icelandic parliament. To close, the radio station Rás 1 is airing an interview September 8 at 9:30pm (21:30). The interview is conducted by the head of the Althingi speech department, Berglind Steinsdóttir. In the interview, Berglind talks to both Inga Rún, our ASR expert, and Steinunn, an Althingi editor. They discuss both sides of the project: software development and user experiences. This broadcast will hopefully give our Icelandic readers and listeners a deeper understanding of the specifics involved in ASR. Thus, we invite you to tune in this Sunday at 21:30.

Practical information about the radio program is below:

Date: Sunday, September 8th @ 21:30 (re-airing Saturday, September 14th 20:45)
Location: Rás 1 website or the radio station
Duration: 30 minutes
Title: “Háttvirtur þingmaður tekur til máls”
Topic: Sjálfvirknivæðing. Gervigreind. Fjórða iðnbyltingin. Hvað kemur þetta ræðum þingmanna við? Tekinn hefur verið í notkun talgreinir sem skrifar upp ræður þingmanna og í þættinum er rætt við Ingu Rún Helgadóttur eðlisfræðing sem hefur tekið þátt í að þróa hann og Steinunni Haraldsdóttur íslenskufræðing sem hefur notað talgreininn.
Language of Interview: Icelandic
Interviewees: Inga Rún Helgadóttir, ASR developer
Steinunn Haraldsdóttir, icelandic specialist who uses the ASR
Interviewer: Berglind Steinsdóttir
Supervisor: Ásdís Emilsdóttir Petersen.

During the interview go to https://ruv.is/ras1 Click on Í BEINNI. Select Rás 1 and press the play button.

SLT 2018 here we come!

This year we’re branching out and attending a smaller conference, IEEE SLT 2018!

We will be presenting the results from our paper, “An Icelandic Pronunciation Dictionary for TTS.” The work was done in collaboration with the linguist and Icelandic specialist, Eiríkur Rögnvaldsson from the University of Iceland.

The paper describes an Icelandic pronunciation dictionary for use in a text-to- speech system for Icelandic. Procedures were implemented to create a consistent training set for grapheme-to-phoneme (g2p) conversion modeling, needed for automatic extensions of the dictionary. The experiments show a clear benefit of using clean data for training, both in terms of PER and in terms of categories of errors made by the g2p algorithm. The results of the dictionary processing were also used to create an initial version of an open source database for Icelandic speech applications. The scripts used in the experiments are available via our Github repository: https://github.com/cadia-lvl/SLT2018.

Jón and Anna Björk’s poster presentation will be at SLT on Friday, Dec. 21 between 10:00 and 12:00 PM. Here’s a sneak peek.
slt_poster_anna_nikulasd_HR

We hope to see you there. If you see Anna or Jón please stop by and say hello.

Language Technology Seminar this Saturday

The cooperation between LVL and other leading icelandic organizations is increasing. Tomorrow Reykjavik University and  Societas Scientiarum Islandica (Vísindafélag Íslendinga) are holding a seminar and panel discussion on the current progress and the future of implementing language technologies for Icelandic.

It will be held at Reykjavik University room M105. Hrafn Loftsson, of LVL, will be moderating the seminar starting at 13:30. It will consist of talks from a professor at University of Iceland, the chairman of Almannaromur, Jón Guðnason of LVL, and the director of Miðeindar ehf. Afterwards is the panel discussion.

We welcome everyone to attend the lively Saturday afternoon discussion!

Researchers’ Night

This Friday is Researchers’ Night (Vísindavaka Rannís 2018). It is an all ages event on the 28th of September, 2018 from 16:30 – 22:00 at Laugardalshöllin, Reykjavik.

We will be there with Reykjavik University demonstrating the possibilities of speech with tech: evaluating collected speech data (Eyra), testing the accuracy of an automatic speech recognizer(ASR) – https://tal.ru.is, listening to a text-to-speech synthesizer, and telling your phone to read the news to you. Come try out the state-of-the-art in Icelandic speech technology, and tell us what you think!

researcher
Researcher by Nick Youngson CC BY-SA 3.0 ImageCreator10