| Bidirectional Recurrent Neural Network with Attention Mechanism for Punctuation Restoration O Tilk, T Alumäe Interspeech 2016, 3047-3051, 2016 | 253 | 2016 |
| LSTM for punctuation restoration in speech transcripts. O Tilk, T Alumäe Interspeech, 683-687, 2015 | 150 | 2015 |
| Advanced rich transcription system for Estonian speech T Alumäe, O Tilk Human language technologies–the Baltic perspective, 1-8, 2018 | 116* | 2018 |
| Event participant modelling with neural networks O Tilk, V Demberg, A Sayeed, D Klakow, S Thater Proceedings of the 2016 Conference on Empirical Methods in Natural Language …, 2016 | 37 | 2016 |
| Modeling under-resourced languages for speech recognition M Kurimo, S Enarvi, O Tilk, M Varjokallio, A Mansikkaniemi, T Alumäe Language Resources and Evaluation 51, 961-987, 2017 | 31 | 2017 |
| Multi-domain recurrent neural network language model for medical speech recognition O Tilk, T Alumäe Human Language Technologies – The Baltic Perspective 268, 149 - 152, 2014 | 26 | 2014 |
| Low-Resource Neural Headline Generation O Tilk, T Alumäe EMNLP 2017 Workshop on New Frontiers in Summarization, 2017 | 15 | 2017 |
| Automatic speech recognition system for Lithuanian broadcast audio T Alumäe, O Tilk Human Language Technologies - the Baltic Perspective : Proceedings of the …, 2016 | 8 | 2016 |
| How to create order in large closed subsets of WordNet-type dictionaries A Lohk, O Tilk, L Võhandu Eesti Rakenduslingvistika Ühingu aastaraamat 9, 149-160, 2013 | 5 | 2013 |
| Neural Networks for Language Modeling and Related Tasks in Low-Resourced Domains and Languages O TILK | | 2018 |
Tanel AlumäeProfessor of Speech Processing, Tallinn University of TechnologyVerified email at taltech.ee
