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Dávid Sztahó
Dávid Sztahó
Budapesti Műszaki és Gazdaságtudományi Egyetem, Távközlési és Médiainformatikai Tanszék
在 vik.bme.hu 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Deep learning methods in speaker recognition: a review
D Sztahó, G Szaszák, A Beke
arXiv preprint arXiv:1911.06615, 2019
742019
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
642008
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
512013
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
352012
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
312017
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
262021
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
262016
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
252022
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
242015
Computer based speech prosody teaching system
D Sztahó, G Kiss, K Vicsi
Computer Speech & Language 50, 126-140, 2018
232018
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
192014
A computer-assisted prosody pronunciation teaching system.
D Sztahó, G Kiss, L Czap, K Vicsi
WOCCI, 45-49, 2014
192014
Automatic classification of emotions in spontaneous speech
D Sztahó, V Imre, K Vicsi
Analysis of Verbal and Nonverbal Communication and Enactment. The Processing …, 2011
192011
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
182012
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
172018
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
162019
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
162011
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
112021
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
102022
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
102016
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