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Ottokar Tilk

https://www.etis.ee/CV/Ottokar_Tilk/est
7.06.1986
6204202
ottokar.tilk@phon.ioc.ee

Teenistuskäik

Töökohad ja ametid
01.01.2017–31.08.2018   
Tallinna Tehnikaülikool, Infotehnoloogia teaduskond, Tarkvarateaduse instituut, Nooremteadur (0,80)
01.06.2015–31.12.2016   
Tallinna Tehnikaülikool, TTÜ Küberneetika Instituut, insener (0,80)
01.02.2015–31.05.2015   
Tallinna Tehnikaülikool, TTÜ Küberneetika Instituut, insener (0,25)
01.10.2013–31.01.2015   
Tallinna Tehnikaülikool, TTÜ Küberneetika Instituut, insener (0,80)
 
 
Haridustee
2012–...   
Tallinna Tehnikaülikool, doktorantuur info- ja kommunikatsioonitehnoloogias
2009–2012   
Tallinna Tehnikaülikool, magistriõpingud informaatikas
2005–2008   
Eesti Infotehnoloogia Kolledž, rakenduskõrgharidusõpe IT süsteemide administreerimises

Kvalifikatsioon

Teaduskraadid
Ottokar Tilk, doktorikraad, 2018, (juh) Tanel Alumäe; Leo Võhandu, Neural Networks for Language Modeling and Related Tasks in Low-Resourced Domains and Languages (Tehisnärvivõrgud keele modelleerimise ja sellega seotud ülesannete jaoks väheste ressurssidega valdkondades ja keeltes), Tallinna Tehnikaülikool, Infotehnoloogia teaduskond, Tarkvarateaduse instituut.
Ottokar Tilk, magistrikraad, 2012, (juh) Leo Võhandu, Iteratiivsel astendamisel põhinevad lahendused mõnedele NP-keerulistele probleemidele suurtel hõredatel maatriksitel, Tallinna Tehnikaülikool, Infotehnoloogia teaduskond, Informaatikainstituut.
 
 
Teadustöö põhisuunad
ETIS KLASSIFIKAATOR: 4. Loodusteadused ja tehnika; 4.6. Arvutiteadused; CERCS KLASSIFIKAATOR: P170 Arvutiteadus, arvutusmeetodid, süsteemid, juhtimine (automaatjuhtimisteooria); TÄPSUSTUS: masinõpe, statistiline keele modelleerimine, tehisnärvivõrgud

Jooksvad projektid

Lõppenud projektid

Publikatsioonid

Klass
Aasta
Publikatsioon
 
2.3.
2018
Tilk, Ottokar (2018). Neural networks for language modeling and related tasks in low-resourced domains and languages. (Doktoritöö, Tallinn University of Technology, School of Information Technologies, Department of Software Science). Tallinn: TTÜ Press.
3.1.
2018
Alumäe, Tanel; Tilk, Ottokar; Asadullah (2018). Advanced rich transcription system for Estonian speech. Human Language Technologies - the Baltic Perspective : Proceedings of the Eighth International Conference, Baltic HLT 2018. Ed. Muischnek, Kadri; Müürisep, Kaili. Amsterdam: IOS Press, 1−8. (Frontiers in Artificial Intelligence and Applications; 307). DOI: 10.3233/978-1-61499-912-6-1.
1.1.
2017
Kurimo, Mikko; Enarvi, Seppo; Tilk, Ottokar; Varjokallio, Matti; Mansikkaniemi, André; Alumäe, Tanel (2017). Modeling under-resourced languages for speech recognition. Language Resources and Evaluation, 51 (4), 961−987.10.1007/s10579-016-9336-9.
3.4.
2017
Tilk, Ottokar; Alumäe, Tanel (2017). Low-resource neural headline generation. EMNLP 2017 Workshop on New Frontiers in Summarization, Proceedings : September 7, 2017, Copenhagen, Denmark. Stroudsburg, PA: Association for Computational Linguistics, 20−26.
3.1.
2016
Tilk, Ottokar; Alumäe, Tanel (2016). Bidirectional recurrent neural network with attention mechanism for punctuation restoration. Interspeech 2016 : Understanding Speech Processing in Human and Machines, September 8-12, 2016, San Francisco, California, Proceedings. Ed. Morgan, Nelson. San Francisco: International Speech Communication Association, 3047−3051.10.21437/Interspeech.2016-1517.
3.1.
2016
Alumäe, Tanel; Tilk, Ottokar (2016). Automatic speech recognition system for Lithuanian broadcast audio. Human Language Technologies - the Baltic Perspective : Proceedings of the Seventh International Conference, Baltic HLT 2016. Ed. Skadina, Inguna; Rozis, Roberts. Amsterdam: IOS Press, 39−45. (Frontiers in Artificial Intelligence and Applications; 289). DOI: 10.3233/978-1-61499-701-6-39.
3.1.
2016
Tilk, Ottokar; Demberg, Vera; Sayeed, Asad; Klakow, Dietrich; Thater, Stefan (2016). Event participant modelling with neural networks. EMNLP 2016: Conference on Empirical Methods in Natural Language Processing, Proceedings, November 1-5, 2016 Austin, Texas, USA. Association for Computational Linguistics, 171−182.
3.1.
2015
Tilk, Ottokar; Alumäe, Tanel (2015). LSTM for punctuation restoration in speech transcripts. INTERSPEECH 2015 : 16th Annual Conference of the International Speech Communication Association : Dresden, Germany, September 6-10, 2015. Ed. Möller, Sebastian; Ney, Hermann; Möbius, Bernd; et al. Dresden: International Speech Communication Association, 683−687.
3.1.
2014
Tilk, Ottokar; Alumäe, Tanel (2014). Multi-domain recurrent neural network language model for medical speech recognition. Human Language Technologies - the Baltic Perspective : Proceedings of the Sixth International Baltic Conference, Baltic HLT 2014. Ed. Utka, Andrius; Grigonytė, Gintarė; Kapočiūtė-Dzikienė, Jurgita; Vaičenonienė, Jurgita. Amsterdam: IOS Press, 149−152. (Frontiers in Artificial Intelligence and Applications; 268). DOI: 10.3233/978-1-61499-442-8-149.
1.1.
2013
Lohk, A.; Tilk, O.; Võhandu, L. (2013). How to create order in large closed subsets of wordnet-type dictionaries. Eesti Rakenduslingvistika Ühingu aastaraamat, 9, 149−160.10.5128/ERYa9.10.
14.11.2018

Ottokar Tilk

https://www.etis.ee/CV/Ottokar_Tilk/eng
7.06.1986
6204202
ottokar.tilk@phon.ioc.ee

Career

Institutions and positions
01.01.2017–31.08.2018   
Tallinn University of Technology , School of Information Technologies, Department of Software Science, Junior Researcher (0,80)
01.06.2015–31.12.2016   
Tallinn University of Technology , Institute of Cybernetics at TUT, Engineer (0,80)
01.02.2015–31.05.2015   
Tallinn University of Technology , Institute of Cybernetics at TUT, Engineer (0,25)
01.10.2013–31.01.2015   
Tallinn University of Technology , Institute of Cybernetics at TUT, Engineer (0,80)
 
 
Education
2012–...   
Tallinn University of Technology, PhD studies in Information and Communication Technology
2009–2012   
Tallinn Technical University, MSc studies in informatics
2005–2008   
Estonian Information Technology College, applied higher education in IT Systems Administration

Qualifications

Academic degrees
Ottokar Tilk, Doctor's Degree, 2018, (sup) Tanel Alumäe; Leo Võhandu, Neural Networks for Language Modeling and Related Tasks in Low-Resourced Domains and Languages, Tallinn University of Technology School of Information Technologies, Department of Software Science.
Ottokar Tilk, Master's Degree, 2012, (sup) Leo Võhandu, Iteratiivsel astendamisel põhinevad lahendused mõnedele NP-keerulistele probleemidele suurtel hõredatel maatriksitel (Power iteration based solutions for some NP-hard problems in large sparse matrices), Tallinn University of Technology School of Information Technologies, Department of Informatics.
 
 
Fields of research
ETIS CLASSIFICATION: 4. Natural Sciences and Engineering; 4.6. Computer Sciences; CERCS CLASSIFICATION: P170 Computer science, numerical analysis, systems, control ; SPECIFICATION: machine learning, statistical language modelling, artificial neural networks
 
 

Projects in progress

Completed projects

Publications

Category
Year
Publication
 
2.3.
2018
Tilk, Ottokar (2018). Neural networks for language modeling and related tasks in low-resourced domains and languages. (Doktoritöö, Tallinn University of Technology, School of Information Technologies, Department of Software Science). Tallinn: TTÜ Press.
3.1.
2018
Alumäe, Tanel; Tilk, Ottokar; Asadullah (2018). Advanced rich transcription system for Estonian speech. Human Language Technologies - the Baltic Perspective : Proceedings of the Eighth International Conference, Baltic HLT 2018. Ed. Muischnek, Kadri; Müürisep, Kaili. Amsterdam: IOS Press, 1−8. (Frontiers in Artificial Intelligence and Applications; 307). DOI: 10.3233/978-1-61499-912-6-1.
1.1.
2017
Kurimo, Mikko; Enarvi, Seppo; Tilk, Ottokar; Varjokallio, Matti; Mansikkaniemi, André; Alumäe, Tanel (2017). Modeling under-resourced languages for speech recognition. Language Resources and Evaluation, 51 (4), 961−987.10.1007/s10579-016-9336-9.
3.4.
2017
Tilk, Ottokar; Alumäe, Tanel (2017). Low-resource neural headline generation. EMNLP 2017 Workshop on New Frontiers in Summarization, Proceedings : September 7, 2017, Copenhagen, Denmark. Stroudsburg, PA: Association for Computational Linguistics, 20−26.
3.1.
2016
Tilk, Ottokar; Alumäe, Tanel (2016). Bidirectional recurrent neural network with attention mechanism for punctuation restoration. Interspeech 2016 : Understanding Speech Processing in Human and Machines, September 8-12, 2016, San Francisco, California, Proceedings. Ed. Morgan, Nelson. San Francisco: International Speech Communication Association, 3047−3051.10.21437/Interspeech.2016-1517.
3.1.
2016
Alumäe, Tanel; Tilk, Ottokar (2016). Automatic speech recognition system for Lithuanian broadcast audio. Human Language Technologies - the Baltic Perspective : Proceedings of the Seventh International Conference, Baltic HLT 2016. Ed. Skadina, Inguna; Rozis, Roberts. Amsterdam: IOS Press, 39−45. (Frontiers in Artificial Intelligence and Applications; 289). DOI: 10.3233/978-1-61499-701-6-39.
3.1.
2016
Tilk, Ottokar; Demberg, Vera; Sayeed, Asad; Klakow, Dietrich; Thater, Stefan (2016). Event participant modelling with neural networks. EMNLP 2016: Conference on Empirical Methods in Natural Language Processing, Proceedings, November 1-5, 2016 Austin, Texas, USA. Association for Computational Linguistics, 171−182.
3.1.
2015
Tilk, Ottokar; Alumäe, Tanel (2015). LSTM for punctuation restoration in speech transcripts. INTERSPEECH 2015 : 16th Annual Conference of the International Speech Communication Association : Dresden, Germany, September 6-10, 2015. Ed. Möller, Sebastian; Ney, Hermann; Möbius, Bernd; et al. Dresden: International Speech Communication Association, 683−687.
3.1.
2014
Tilk, Ottokar; Alumäe, Tanel (2014). Multi-domain recurrent neural network language model for medical speech recognition. Human Language Technologies - the Baltic Perspective : Proceedings of the Sixth International Baltic Conference, Baltic HLT 2014. Ed. Utka, Andrius; Grigonytė, Gintarė; Kapočiūtė-Dzikienė, Jurgita; Vaičenonienė, Jurgita. Amsterdam: IOS Press, 149−152. (Frontiers in Artificial Intelligence and Applications; 268). DOI: 10.3233/978-1-61499-442-8-149.
1.1.
2013
Lohk, A.; Tilk, O.; Võhandu, L. (2013). How to create order in large closed subsets of wordnet-type dictionaries. Eesti Rakenduslingvistika Ühingu aastaraamat, 9, 149−160.10.5128/ERYa9.10.
14.11.2018

Otsi projekti

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Asutus on projekti finantseerija   Asutus on projekti teostaja  
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Kõik   Tavaprojektid   Ülemprojektid   Alamprojektid  
Uus Frascati (2015)
Uus ja vana Frascati (otsing uue järgi väljastab ka seotud vanad)
Kõik
Käimasolevad
Lõppenud
Algus
Hajus
Täpne
Uus otsing (Beetaversioon) Lihtotsing Tühjenda
  • Leitud 4 kirjet
ProgrammLiikNumberNimiProjekti algusProjekti lõppVastutav täitjaAsutusFinantseerijapoolne rahastamine
TKTAR16020Eesti-uuringute Tippkeskus01.01.201501.03.2023Einar MeisterTallinna Tehnikaülikool, Infotehnoloogia teaduskond, Tarkvarateaduse instituut118 163,57 EUR
EKTEKT87Kõnetuvastus 201.01.201531.12.2017Tanel AlumäeTallinna Tehnikaülikool, TTÜ Küberneetika Instituut; Tallinna Tehnikaülikool, Infotehnoloogia teaduskond, Tarkvarateaduse instituut97 765,00 EUR
SFSF0140007s12Usaldusväärsed tarkvara- ja inimkeeletehnoloogiad01.01.201231.12.2014Tarmo UustaluTallinna Tehnikaülikool, TTÜ Küberneetika Instituut514 620,00 EUR
2.2.V18035Uurmis- ja arendustöö kokkulepe01.02.201831.08.2018Tanel AlumäeTallinna Tehnikaülikool, Infotehnoloogia teaduskond, Tarkvarateaduse instituut13 600,00 EUR