| Automatic estimation of severity of Parkinson's disease based on speech rhythm related features D Sztahó, MG Tulics, K Vicsi, I Valálik 2017 8th IEEE International Conference on Cognitive Infocommunications …, 2017 | 31 | 2017 |
| Deep learning solution for pathological voice detection using LSTM-based autoencoder hybrid with multi-task learning KG Dávid Sztahó, TM Gábriel I14th International Joint Conference on Biomedical Engineering Systems and …, 2021 | 26 | 2021 |
| Language independent detection possibilities of depression by speech G Kiss, MG Tulics, D Sztahó, A Esposito, K Vicsi Recent advances in nonlinear speech processing, 103-114, 2016 | 26 | 2016 |
| Phonetic-class based correlation analysis for severity of dysphonia MG Tulics, K Vicsi 8th International Conference on Cognitive InfoCommunications: CogInfoCom …, 2017 | 18 | 2017 |
| The automatic assessment of the severity of dysphonia MG Tulics, K Vicsi International Journal of Speech Technology 22, 341-350, 2019 | 16 | 2019 |
| Artificial neural network and svm based voice disorder classification MG Tulics, G Szaszák, K Mészáros, K Vicsi 2019 10th IEEE International Conference on Cognitive Infocommunications …, 2019 | 13 | 2019 |
| Separation of several illnesses using correlation structures with convolutional neural networks AZ Jenei, G Kiss, MG Tulics, D Sztahó Acta Polytechnica Hungarica 18 (7), 47-66, 2021 | 11 | 2021 |
| Automatic discrimination of several types of speech pathologies D Sztahó, G Kiss, MG Tulics, B Hajduska-Dér, K Vicsi 2019 International Conference on Speech Technology and Human-Computer …, 2019 | 9 | 2019 |
| Automatic classification possibilities of the voices of children with dysphonia MG Tulics, K Vicsi Infocommunications Journal 10 (No.3), pp. 30-36. , 7 p., 2018 | 8 | 2018 |
| Statistical analysis of acoustical parameters in the voice of children with juvenile dysphonia MG Tulics, F Kazinczi, K Vicsi Speech and Computer: 18th International Conference, SPECOM 2016, Budapest …, 2016 | 8 | 2016 |
| Using ASR posterior probability and acoustic features for voice disorder classification MG Tulics, G Szaszák, K Mészáros, K Vicsi 2020 11th IEEE International Conference on Cognitive Infocommunications …, 2020 | 6 | 2020 |
| Automatic separation of various disease types by correlation structure of time shifted speech features D Sztahó, G Kiss, MG Tulics, K Vicsi 2018 41st International Conference on Telecommunications and Signal …, 2018 | 6 | 2018 |
| Cross-lingual detection of dysphonic speech for Dutch and Hungarian datasets D Sztahó, MG Tulics, J Qi, K Vicsi Proceedings of the 15th International Joint Conference on Biomedical …, 2022 | 3 | 2022 |
| Possibilities for the automatic classification of functional and organic dysphonia MG Tulics, LJ Lavati, K Mészáros, K Vicsi 2019 International Conference on Speech Technology and Human-Computer …, 2019 | 3 | 2019 |
| Analyzing f0 discontinuity for speech prosody enhancement G Szaszák, MG Tulics, MA Tündik Acta Univ. Sapientiae Elect. Mech. Eng 6 (1), 59-67, 2014 | 3 | 2014 |
| Application for Detecting Depression, Parkinson's Disease and Dysphonic Speech. G Kiss, D Sztahó, MG Tulics Interspeech, 956-957, 2021 | 2 | 2021 |
| Analysis of cross disorder severity prediction problems based on speech features G Kiss, MG Tulics, AZ Jenei, D Sztahó PROCEEDINGS E REPORT 71, 2021 | 1 | 2021 |
| A diszfónia és automatikus felismerése TM Gábriel beszéd• kuTaTás• alkalmazás, 35, 2021 | 1 | 2021 |
| Automatic classification of dysphonia MG Tulics, K Vicsi PhD-értekezés. BME, Budapest, 2020 | 1 | 2020 |
| Jövőbe látó lélektan–Gépi tanulás a pszichológiai kutatásmódszertanban A Damsa, M Püski, MG Tulics Magyar Pszichológiai Szemle 79 (1), 1-18, 2024 | | 2024 |
