| Analysis of 2d feature spaces for deep learning-based speech recognition G Korvel, P Treigys, G Tamulevicus, J Bernataviciene, B Kostek Journal of the Audio Engineering Society 66 (12), 1072-1081, 2018 | 48 | 2018 |
| Neural natural language generation: A survey on multilinguality, multimodality, controllability and learning E Erdem, M Kuyu, S Yagcioglu, A Frank, L Parcalabescu, B Plank, A Babii, ... Journal of Artificial Intelligence Research 73, 1131-1207, 2022 | 37 | 2022 |
| A study of cross-linguistic speech emotion recognition based on 2D feature spaces G Tamulevičius, G Korvel, AB Yayak, P Treigys, J Bernatavičienė, ... Electronics 9 (10), 1725, 2020 | 32 | 2020 |
| Machine learning-based analysis of English lateral allophones M Piotrowska, G Korvel, B Kostek, T Ciszewski, A Czyżewski International Journal of Applied Mathematics and Computer Science 29 (2 …, 2019 | 18 | 2019 |
| Evaluation of aspiration problems in L2 English pronunciation employing machine learning M Piotrowska, A Czyżewski, T Ciszewski, G Korvel, A Kurowski, B Kostek The Journal of the Acoustical Society of America 150 (1), 120-132, 2021 | 15 | 2021 |
| Machine learning based classification of colorectal cancer tumour tissue in whole-slide images M Morkūnas, P Treigys, J Bernatavičienė, A Laurinavičius, G Korvel Informatica 29 (1), 75-90, 2018 | 15 | 2018 |
| Evaluation of Lombard speech models in the context of speech in noise enhancement G Korvel, K Kąkol, O Kurasova, B Kostek IEEE access 8, 155156-155170, 2020 | 13 | 2020 |
| Speech analytics based on machine learning G Korvel, A Kurowski, B Kostek, A Czyzewski Machine Learning Paradigms: Advances in Data Analytics, 129-157, 2019 | 13 | 2019 |
| Examining feature vector for phoneme recognition G Korvel, B Kostek 2017 IEEE international symposium on signal processing and information …, 2017 | 13 | 2017 |
| Developing models of Lithuanian speech vowels and semivowels G Pyž, V Šimonytė, V Slivinskas Informatica 25 (1), 55-72, 2014 | 12 | 2014 |
| Highlighting interlanguage phoneme differences based on similarity matrices and convolutional neural network G Korvel, P Treigys, B Kostek The Journal of the Acoustical Society of America 149 (1), 508-523, 2021 | 10 | 2021 |
| Improving objective speech quality indicators in noise conditions K Kąkol, G Korvel, B Kostek Data Science: New Issues, Challenges and Applications, 199-218, 2020 | 7 | 2020 |
| Voiceless stop consonant modelling and synthesis framework based on MISO dynamic system G Korvel, B Kostek Archives of Acoustics 42, 375-383, 2017 | 7 | 2017 |
| A phoneme harmonic generator G Korvel, V Šimonytė, V Slivinskas Information Technology and Control 45 (1), 7-12, 2016 | 6 | 2016 |
| A modified additive synthesis method using source-filter model G Korvel, V Šimonyte, V Slivinskas Journal of the Audio Engineering Society 63 (6), 443-450, 2015 | 6 | 2015 |
| Modelling of Lithuanian speech diphthongs G Pyž, V Šimonytė, V Slivinskas Informatica 22 (3), 411-434, 2011 | 6 | 2011 |
| Discovering rule-based learning systems for the purpose of music analysis G Korvel, B Kostek Proceedings of Meetings on Acoustics 39 (1), 2019 | 5 | 2019 |
| Investigating feature spaces for isolated word recognition P Treigys, G Korvel, G Tamulevičius, J Bernatavičienė, B Kostek Data science: New issues, challenges and applications, 165-181, 2020 | 4 | 2020 |
| Comparative analysis of spectral and cepstral feature extraction techniques for phoneme modelling G Korvel, O Kurasova, B Kostek Multimedia and Network Information Systems: Proceedings of the 11th …, 2019 | 4 | 2019 |
| Lithuanian speech synthesis by computer using additive synthesis G Pyz, V Simonyte, V Slivinskas Elektronika ir Elektrotechnika 18 (8), 77-80, 2012 | 4 | 2012 |
