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Mitmekeelne masintõlge ressursivaestele keeltele
No full textVäitekirja elektrooniline versioon ei sisalda publikatsiooneKujutlege maailma, kus igal keelel on arenenud loomuliku keele rakendused nagu ChatGPT või on esindatud Google'i tõlkemootoris, hoolimata nende suurusest. See on visioon minu doktoritöö taga, mis keskendub väheste ressurssidega keelte masintõlkele, mille põhifookus on just soome-ugri keeltel. Soome-ugri keelte perekonnas on üle 40 keele ja rääkijaid üle 20 miljoni inimese Euroopas ja Põhja-Aasias. Need keeled, alates eesti, soome või ungari rahvuskeeltest kuni väiksemate kohalike keelteni nagu võru, liivi või komi, kannavad endas rikkalikke kultuuripärandeid, kuid seisavad silmitsi märkimisväärse digitaalse mahajäämisega.
Minu doktoritöö ülesanne on vähendada lõhet suurte ja väikeste keelte vahel, arendades välja tehisnärvivõrkudel põhinevad masintõlkesüsteemid keeleressursivaeste keelte jaoks. Doktoritöö keskendub ressursirohketest ressursivaeste keelteni, kasutades uusimaid teaduslikult tõestatud meetodeid, et lahendada andmete vähesusest ning tõlke kvaliteedi ja effektiivsusega seotud probleeme. Doktoritöös välja toodud süsteemid toetavad 23 soome-ugri keelt ning toetavad seeläbi avalikku juurdepääsu teabele ja teenustele väikestes kogukondades.
Selle doktoritöö praktiline tulemus on olnud oluline, eriti eesti-kesksete tõlkimisvahendite arendamisel, mis suudavad konkureerida Google'i ja DeepL'i tõlkesüsteemidega. Eesti avalik sektor on need süsteemid kasutusele võtnud, näidates nende tõhusust igapäevaolukordades. Lisaks riiklikule kasutusele on kõik töös välja töötatud mudelid avatud litsensiga, võimaldades tehtud tööd teistel kasutusele võtta ja edasi arendada.
See töö demonstreerib, kuidas tehnoloogia aitab tagada võrdse juurdepääsu digitaalsetele ressurssidele igas keeles. Oleme ehitamas kaasavamat digitaalset keskkonda, tagades, et väiksemaid keeli ei jäeta tähelepanuta. Uurimus ei tõsta ainult keeletehnoloogia piire, vaid rõhutab ka keelelise mitmekesisuse väärtust tehnoloogilises edus. See on samm tuleviku suunas, kus ühtegi keelt ei jäeta digitaalajastul maha.Imagine a world where every language has advanced natural language applications like ChatGPT or is present in Google Translate, no matter how small. This is the vision behind my research, which delves into machine translation for the Finno-Ugric languages—a language family with over 40 different languages, spoken by over 20 million people across Europe and North Asia. These languages, from Estonian, Finnish, or Hungarian national languages to more minor local languages like Võro, Livonian, or Komi, carry rich cultural legacies but face significant digital neglect.
My doctoral work addresses this gap by developing robust neural machine translation systems tailored for these languages. With a focus on languages ranging from higher to lesser-known under-resourced languages, the research uses state-of-the-art NLP techniques to overcome data scarcity and enhance translation accuracy and efficiency. The final systems in work support translation for 23 Finno-Ugric languages, bringing the benefits of advanced translation technology to a diverse range of communities.
The practical outcome of this thesis has been significant, especially with the development of Estonian-centric translation tools that can compete with the likes of Google Translate and DeepL. The Estonian government has adopted these systems, showcasing their effectiveness in real-world scenarios. Beyond governmental use, these translation models provide communities access to information and services in their native languages, supporting cultural preservation and participation in the digital world.
This work demonstrates how technology can help bring equal access to digital resources for all languages. We're building a more inclusive digital environment by ensuring minor languages aren't overlooked. The research not only pushes the boundaries of NLP technology but also emphasizes the importance of valuing linguistic diversity in technological progress. It's a step towards a future where no language is left behind in the digital age.https://www.ester.ee/record=b574399
Telegram-based Russian hacktivism as a new phenomenon and the influence of media visibility on target selection
No full textRussia's full-scale invasion of Ukraine in February 2022 resulted in a rise in cyber threats and initiated a continuing surge of coordinated cyberattacks by Russian-speaking hacktivist groups targeting countries expressing solidarity with Ukraine. This thesis explores the emergence of Telegram-based Russian hacktivism following the full-scale invasion of Ukraine in 2022 and examines the extent to which domestic media coverage influences the frequency of cyberattacks claimed by these groups. While prior academic literature has focused on hacktivism as the use of the internet to promote or resist sociopolitical agendas due to ideological beliefs, often targeting cyberspace itself as a means to achieve social change, this thesis argues that a distinct new era of hacktivism has emerged. This Telegram-based Russian hacktivism is characterized by centralized, openly malicious collectives operating through Telegram, combining geopolitical motives with financial incentives and media-driven strategies. The thesis employs a mixed-methods research design consisting of a qualitative and quantitative analysis. The qualitative exploration of the phenomenon reveals that post-2022 Russian hacktivist groups operate in a reactive and opportunistic manner, frequently targeting civilian infrastructure with low-sophistication attacks such as DDoS, while seeking visibility and legitimacy through public announcements and propaganda. The quantitative component evaluates the relationship between media coverage and attack frequency using two original datasets: over 20,000 claimed cyberattacks and more than 5,500 media articles across 16 EU countries. The findings show a generally positive but inconsistent correlation between media visibility and cyberattacks, with clear evidence in some cases (e.g., Germany, Slovenia) that media attention precedes increased targeting. However, other cases suggest that strategic or geopolitical relevance may override visibility as the primary driver of attacks.https://www.ester.ee/record=b5753314*es
Õppijakeskne vaade virtuaalreaalsuse kasutamisele kutseõppes
No full texthttps://www.ester.ee/record=b5756859*es
Sideandmete kasutamine lubatava tõendina süüteomenetluses
No full texthttps://www.ester.ee/record=b5751402*es
Estonian Russophone Identity in 2010
No full textIn 2010, the dominant identity discourse among Russophones in Estonia centered around con-structing a distinct identity from their significant Others while consequently battling socio-economic inequality. Estonian Russophones did not perceive themselves as belonging anywhere. Instead, Estonian Russophone identity construction unfolded through cultural development that differentiated them from their significant Others. Aspirations for political representation and improvement of Russophones economic conditions remain salient, particularly due to financial crises of the time and perceived socio-economic exclusion. This report will begin with the de-scription of the selected sources, continue into the detailed description of the identity categories retrieved during the data analysis, highlighting the dominant discourses presented in the selected texts
Arvamused eestikeelsete e-kirjade keeleliste valikute kohta
No full texthttps://www.ester.ee/record=b5752372*es
Õpetajate kiusamine õpilaste poolt kahe Tartu linna kooli näitel
No full texthttps://www.ester.ee/record=b5751281*es
Tarkvaraprojektide tulemuspõhise hinnastamise võimaldajad ja takistused
No full textThis article investigates the enablers and barriers to performance-based pricing for software projects in Estonia through qualitative interviews (N=7) conducted with software company leaders. Findings reveal time-and-materials pricing prevails due to flexibility, despite recognized incentive misalignments. Performance-based pricing adoption faces significant barriers, including difficulties in quantifying value, high perceived risks for both parties, insufficient trust, and restrictive procurement norms. Critical enablers involve strong client partnerships, clear value propositions, measurable outcomes, and structured risk-sharing agreements. The research offers empirical insights into performance-based pricing challenges specifically within project-based services, emphasizing trust and context as crucial for implementing value-aligned, often hybrid, pricing models