The strategic impact of META-NET on the regional, national and international level

This article provides an overview of the dissemination work carried out in META-NET from 2010 until 2015; we describe its impact on the regional, national and international level, mainly with regard to politics and the funding situation for LT topics. The article documents the initiative's work throughout Europe in order to boost progress and innovation in our field.Peer ReviewedPostprint (author's final draft

Corpora for Bilingual Terminology Extraction in Cybersecurity Domain

The paper aims at presenting English-Lithuanian corpora for bilingual term extraction (BiTE) in the cybersecurity domain within the framework of the project DVITAS. It is argued that a system of parallel, comparable, and training corpora for BiTE is particularly useful for less resourced languages, as it allows to efficiently use strengths and avoid weaknesses of comparable and parallel resources. A special focus is given to the open nature of the data, which is achieved by publishing the data in CLARIN-LT repository

The strategic impact of META-NET on the regional, national and international level

This article provides an overview of the dissemination work carried out in META-NET from 2010 until early 2014; we describe its impact on the regional, national and international level, mainly with regard to politics and the situation of funding for LT topics. This paper documents the initiative’s work throughout Europe in order to boost progress and innovation in our field.Postprint (published version

Põhiemotsioonid eestikeelses etteloetud kõnes: akustiline analüüs ja modelleerimine

Väitekirja elektrooniline versioon ei sisalda publikatsiooneDoktoritööl oli kaks eesmärki: saada teada, milline on kolme põhiemotsiooni – rõõmu, kurbuse ja viha – akustiline väljendumine eestikeelses etteloetud kõnes, ning luua neile uurimistulemustele tuginedes eestikeelsele kõnesüntesaatorile parameetrilise sünteesi jaoks emotsionaalse kõne akustilised mudelid, mis aitaksid süntesaatoril äratuntavalt nimetatud emotsioone väljendada. Kuna sünteeskõnet rakendatakse paljudes valdkondades, näiteks inimese ja masina suhtluses, multimeedias või puuetega inimeste abivahendites, siis on väga oluline, et sünteeskõne kõlaks loomulikuna, võimalikult inimese rääkimise moodi. Üks viis sünteeskõne loomulikumaks muuta on lisada sellesse emotsioone, tehes seda mudelite abil, mis annavad süntesaatorile ette emotsioonide väljendamiseks vajalikud akustiliste parameetrite väärtuste kombinatsioonid. Emotsionaalse kõne mudelite loomiseks peab teadma, kuidas emotsioonid inimkõnes hääleliselt väljenduvad. Selleks tuli uurida, kas, millisel määral ja mis suunas emotsioonid akustiliste parameetrite (näiteks põhitooni, intensiivsuse ja kõnetempo) väärtusi mõjutavad ning millised parameetrid võimaldavad emotsioone üksteisest ja neutraalsest kõnest eristada. Saadud tulemuste põhjal oli võimalik luua emotsioonide akustilisi mudeleid* ning katseisikud hindasid, milliste mudelite järgi on emotsioonid sünteeskõnes äratuntavad. Eksperiment kinnitas, et akustikaanalüüsi tulemustele tuginevate mudelitega suudab eestikeelne kõnesüntesaator rahuldavalt väljendada nii kurbust kui ka viha, kuid mitte rõõmu. Doktoritöö kajastab üht võimalikku viisi, kuidas rõõm, kurbus ja viha eestikeelses kõnes hääleliselt väljenduvad, ning esitab mudelid, mille abil emotsioone eestikeelsesse sünteeskõnesse lisada. Uurimistöö on lähtepunkt edasisele eestikeelse emotsionaalse sünteeskõne akustiliste mudelite arendamisele. * Katsemudelite järgi sünteesitud emotsionaalset kõnet saab kuulata aadressil https://www.eki.ee/heli/index.php?option=com_content&view=article&id=7&Itemid=494.The present doctoral dissertation had two major purposes: (a) to find out and describe the acoustic expression of three basic emotions – joy, sadness and anger – in read Estonian speech, and (b) to create, based on the resulting description, acoustic models of emotional speech, designed to help parametric synthesis of Estonian speech recognizably express the above emotions. As far as synthetic speech has many applications in different fields, such as human-machine interaction, multimedia, or aids for the disabled, it is vital that the synthetic speech should sound natural, that is, as human-like as possible. One of the ways to naturalness lies through adding emotions to the synthetic speech by means of models feeding the synthesiser with combinations of acoustic parametric values necessary for emotional expression. In order to create such models of emotional speech, it is first necessary to have a detailed knowledge of the vocal expression of emotions in human speech. For that purpose I had to investigate to what extent, if any, and in what direction emotions influence the values of speech acoustic parameters (e.g., fundamental frequency, intensity and speech rate), and which parameters enable discrimination of emotions from each other and from neutral speech. The results provided material for creating acoustic models of emotions* to be presented to evaluators, who were asked to decide which of the models helped to produce synthetic speech with recognisable emotions. The experiment proved that with models based on acoustic results, an Estonian speech synthesiser can satisfactorily express sadness and anger, while joy was not so well recognised by listeners. This doctoral dissertation describes one of the possible ways for the vocal expression of joy, sadness and anger in Estonian speech and presents some models enabling addition of emotions to Estonian synthetic speech. The study serves as a starting point for the future development of acoustic models for Estonian emotional synthetic speech. * Recorded examples of emotional speech synthesised using the test models can be accessed at https://www.eki.ee/heli/index.php?option=com_content&view=article&id=7&Itemid=494

Eesti keele üldvaldkonna tekstide laia kattuvusega automaatne sündmusanalüüs

Seoses tekstide suuremahulise digitaliseerimisega ning digitaalse tekstiloome järjest laiema levikuga on tohutul hulgal loomuliku keele tekste muutunud ja muutumas masinloetavaks. Masinloetavus omab potentsiaali muuta tekstimassiivid inimeste jaoks lihtsamini hallatavaks, nt lubada rakendusi nagu automaatne sisukokkuvõtete tegemine ja tekstide põhjal küsimustele vastamine, ent paraku ei ulatu praegused automaatanalüüsi võimalused tekstide sisu tegeliku mõistmiseni. Oletatakse, tekstide sisu mõistvale automaatanalüüsile viib meid lähemale sündmusanalüüs – kuna paljud tekstid on narratiivse ülesehitusega, tõlgendatavad kui „sündmuste kirjeldused”, peaks tekstidest sündmuste eraldamine ja formaalsel kujul esitamine pakkuma alust mitmete „teksti mõistmist” nõudvate keeletehnoloogia rakenduste loomisel. Käesolevas väitekirjas uuritakse, kuivõrd saab eestikeelsete tekstide sündmusanalüüsi käsitleda kui avatud sündmuste hulka ja üldvaldkonna tekste hõlmavat automaatse lingvistilise analüüsi ülesannet. Probleemile lähenetakse eesti keele automaatanalüüsi kontekstis uudsest, sündmuste ajasemantikale keskenduvast perspektiivist. Töös kohandatakse eesti keelele TimeML märgendusraamistik ja luuakse raamistikule toetuv automaatne ajaväljendite tuvastaja ning ajasemantilise märgendusega (sündmusviidete, ajaväljendite ning ajaseoste märgendusega) tekstikorpus; analüüsitakse korpuse põhjal inimmärgendajate kooskõla sündmusviidete ja ajaseoste määramisel ning lõpuks uuritakse võimalusi ajasemantika-keskse sündmusanalüüsi laiendamiseks geneeriliseks sündmusanalüüsiks sündmust väljendavate keelendite samaviitelisuse lahendamise näitel. Töö pakub suuniseid tekstide ajasemantika ja sündmusstruktuuri märgenduse edasiarendamiseks tulevikus ning töös loodud keeleressurssid võimaldavad nii konkreetsete lõpp-rakenduste (nt automaatne ajaküsimustele vastamine) katsetamist kui ka automaatsete märgendustööriistade edasiarendamist.  Due to massive scale digitalisation processes and a switch from traditional means of written communication to digital written communication, vast amounts of human language texts are becoming machine-readable. Machine-readability holds a potential for easing human effort on searching and organising large text collections, allowing applications such as automatic text summarisation and question answering. However, current tools for automatic text analysis do not reach for text understanding required for making these applications generic. It is hypothesised that automatic analysis of events in texts leads us closer to the goal, as many texts can be interpreted as stories/narratives that are decomposable into events. This thesis explores event analysis as broad-coverage and general domain automatic language analysis problem in Estonian, and provides an investigation starting from time-oriented event analysis and tending towards generic event analysis. We adapt TimeML framework to Estonian, and create an automatic temporal expression tagger and a news corpus manually annotated for temporal semantics (event mentions, temporal expressions, and temporal relations) for the language; we analyse consistency of human annotation of event mentions and temporal relations, and, finally, provide a preliminary study on event coreference resolution in Estonian news. The current work also makes suggestions on how future research can improve Estonian event and temporal semantic annotation, and the language resources developed in this work will allow future experimentation with end-user applications (such as automatic answering of temporal questions) as well as provide a basis for developing automatic semantic analysis tools

Terminology Integration in Statistical Machine Translation

Elektroniskā versija nesatur pielikumusPromocijas darbs apraksta autora izpētītas metodes un izstrādātus rīkus divvalodu terminoloģijas integrācijai statistiskās mašīntulkošanas sistēmās. Autors darbā piedāvā inovatīvas metodes terminu integrācijai SMT sistēmu trenēšanas fāzē (ar statiskas integrācijas palīdzību) un tulkošanas fāzē (ar dinamiskas integrācijas palīdzību). Darbā uzmanība pievērsta ne tikai metodēm terminu integrācijai SMT, bet arī metodēm valodas resursu, kas nepieciešami dažādu uzdevumu veikšanai terminu integrācijas SMT darbplūsmās, ieguvei. Piedāvātās metodes ir novērtētas automātiskas un manuālas novērtēšanas eksperimentos. Iegūtie rezultāti parāda, ka statiskās un dinamiskās integrācijas metodes ļauj būtiski uzlabot tulkošanas kvalitāti. Darbā aprakstītie rezultāti ir aprobēti vairākos pētniecības projektos un ieviesti praktiskos risinājumos. Atslēgvārdi: statistiskā mašīntulkošana, terminoloģija, starpvalodu informācijas izvilkšanaThe doctoral thesis describes methods and tools researched and developed by the author for bilingual terminology integration into statistical machine translation systems. The author presents novel methods for terminology integration in SMT systems during training (through static integration) and during translation (through dynamic integration). The work focusses not only on the SMT integration techniques, but also on methods for acquisition of linguistic resources that are necessary for different tasks involved in workflows for terminology integration in SMT systems. The proposed methods have been evaluated using automatic and manual evaluation methods. The results show that both static and dynamic integration methods allow increasing translation quality. The thesis describes also areas where the methods have been approbated in practice. Keywords: statistical machine translation, terminology, cross-lingual information extractio

Building of Parallel and Comparable Cybersecurity Corpora for Bilingual Terminology Extraction

CC-BY 4.0The paper aims at presenting English-Lithuanian corpora for bilingual term extraction (BiTE) in the cybersecurity domain within the framework of the project DVITAS. It is argued that a system of parallel, comparable, and training corpora for BiTE is particularly useful for less-resourced languages, as it allows efficiently to combine strengths and avoid weaknesses of comparable and parallel resources. A special focus is given to the availability of sources in the cybersecurity domain and issues related to copyright-protected publications, as well as the data curation performed for building the corpora and depositing them to CLARIN-LT repository

Leveraging bilingual terminology to improve machine translation in a CAT environment

This work focuses on the extraction and integration of automatically aligned bilingual terminology into a Statistical Machine Translation (SMT) system in a Computer Aided Translation (CAT) scenario. We evaluate the proposed framework that, taking as input a small set of parallel documents, gathers domain-specific bilingual terms and injects them into an SMT system to enhance translation quality. Therefore, we investigate several strategies to extract and align terminology across languages and to integrate it in an SMT system. We compare two terminology injection methods that can be easily used at run-time without altering the normal activity of an SMT system: XML markup and cache-based model. We test the cache-based model on two different domains (information technology and medical) in English, Italian and German, showing significant improvements ranging from 2.23 to 6.78 BLEU points over a baseline SMT system and from 0.05 to 3.03 compared to the widely-used XML markup approach