Deep learning methods in speaker recognition: a review D Sztahó, G Szaszák, A Beke arXiv preprint arXiv:1911.06615, 2019 | 70 | 2019 |
Speech emotion perception by human and machine SL Tóth, D Sztahó, K Vicsi Verbal and Nonverbal Features of Human-Human and Human-Machine Interaction …, 2008 | 62 | 2008 |
Language independent automatic speech segmentation into phoneme-like units on the base of acoustic distinctive features G Kiss, D Sztahó, K Vicsi 2013 IEEE 4th international conference on cognitive infocommunications …, 2013 | 50 | 2013 |
Examination of the sensitivity of acoustic-phonetic parameters of speech to depression K Vicsi, D Sztahó, G Kiss 2012 IEEE 3rd International Conference on Cognitive Infocommunications …, 2012 | 32 | 2012 |
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 | 28 | 2017 |
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 | 25 | 2016 |
Estimating the severity of parkinson's disease from speech using linear regression and database partitioning. D Sztahó, G Kiss, K Vicsi INTERSPEECH, 498-502, 2015 | 24 | 2015 |
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 | 22 | 2021 |
Computer based speech prosody teaching system D Sztahó, G Kiss, K Vicsi Computer Speech & Language 50, 126-140, 2018 | 22 | 2018 |
Automatic assessment of the degree of clinical depression from speech using X-vectors JV Egas-López, G Kiss, D Sztahó, G Gosztolya ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 21 | 2022 |
Connection between body condition and speech parameters-especially in the case of hypoxia G Kiss, D Sztahó, K Vicsi, A Golemis 2014 5th IEEE Conference on Cognitive Infocommunications (CogInfoCom), 333-336, 2014 | 19 | 2014 |
A computer-assisted prosody pronunciation teaching system. D Sztahó, G Kiss, L Czap, K Vicsi WOCCI, 45-49, 2014 | 19 | 2014 |
Automatic classification of emotions in spontaneous speech D Sztahó, V Imre, K Vicsi Analysis of Verbal and Nonverbal Communication and Enactment. The Processing …, 2011 | 19 | 2011 |
Detection Possibilities of Depression and Parkinson’s disease Based on the Ratio of Transient Parts of the Speech G Kiss, AB Takács, D Sztahó, K Vicsi 2018 9th IEEE International Conference on Cognitive Infocommunications …, 2018 | 16 | 2018 |
Recognition of Emotions on the Basis of Different Levels of Speech Segments. K Vicsi, D Sztahó J. Adv. Comput. Intell. Intell. Informatics 16 (2), 335-340, 2012 | 16 | 2012 |
Parkinson’s disease severity estimation on hungarian speech using various speech tasks D Sztahó, I Valálik, K Vicsi 2019 International Conference on Speech Technology and Human-Computer …, 2019 | 15 | 2019 |
Problems of the automatic emotion recognitions in spontaneous speech; an example for the recognition in a dispatcher center K Vicsi, D Sztahó Toward Autonomous, Adaptive, and Context-Aware Multimodal Interfaces …, 2011 | 15 | 2011 |
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 | 10 | 2021 |
Estimating the severity of Parkinson’s disease using voiced ratio and nonlinear parameters D Sztahó, K Vicsi International Conference on Statistical Language and Speech Processing, 96-107, 2016 | 10 | 2016 |
The applicability of the Beck Depression Inventory and Hamilton Depression Scale in the automatic recognition of depression based on speech signal processing B Hajduska-Dér, G Kiss, D Sztahó, K Vicsi, L Simon Frontiers in psychiatry 13, 879896, 2022 | 9 | 2022 |