Laszlo Toth
Laszlo Toth
Research Group on Artificial Intelligence
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A speech recognition-based solution for the automatic detection of mild cognitive impairment from spontaneous speech
L Tóth, I Hoffmann, G Gosztolya, V Vincze, G Szatlóczki, Z Bánréti, ...
Current Alzheimer Research 15 (2), 130-138, 2018
Identifying mild cognitive impairment and mild Alzheimer’s disease based on spontaneous speech using ASR and linguistic features
G Gosztolya, V Vincze, L Tóth, M Pákáski, J Kálmán, I Hoffmann
Computer Speech & Language 53, 181-197, 2019
Automatic detection of mild cognitive impairment from spontaneous speech using ASR
L Tóth, G Gosztolya, V Vincze, I Hoffmann, G Szatlóczki
ISCA, 2015
Kernel-based feature extraction with a speech technology application
A Kocsor, L Tóth
IEEE Transactions on Signal Processing 52 (8), 2250-2263, 2004
Phone recognition with hierarchical convolutional deep maxout networks
L Tóth
EURASIP Journal on Audio, Speech, and Music Processing 2015, 1-13, 2015
Phone recognition with deep sparse rectifier neural networks
L Tóth
2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013
Combining time-and frequency-domain convolution in convolutional neural network-based phone recognition
L Tóth
2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014
DNN-based ultrasound-to-speech conversion for a silent speech interface
TG Csapó, T Grósz, G Gosztolya, L Tóth, A Markó
International Speech Communication Association (ISCA), 2017
Assessing the degree of nativeness and Parkinson's condition using Gaussian processes and deep rectifier neural networks
T Grósz, R Busa-Fekete, G Gosztolya, L Tóth
szte, 2015
Detecting autism, emotions and social signals using AdaBoost
G Gosztolya, R Busa-Fekete, L Tóth
Interspeech, 2013
A comparison of deep neural network training methods for large vocabulary speech recognition
L Tóth, T Grósz
Text, Speech, and Dialogue: 16th International Conference, TSD 2013, Pilsen …, 2013
Convolutional deep maxout networks for phone recognition
L Tóth
Fifteenth Annual Conference of the International Speech Communication …, 2014
Increasing the robustness of CNN acoustic models using autoregressive moving average spectrogram features and channel dropout
G Kovács, L Tóth, D Van Compernolle, S Ganapathy
Pattern Recognition Letters 100, 44-50, 2017
Cross-lingual Portability of MLP-Based Tandem Features--A Case Study for English and Hungarian
L Tóth, J Frankel, G Gosztolya, S King
Detecting mild cognitive impairment from spontaneous speech by correlation-based phonetic feature selection
G Gosztolya, L Tóth, T Grósz, V Vincze, I Hoffmann, G Szatlóczki, ...
szte, 2016
DNN-based feature extraction and classifier combination for child-directed speech, cold and snoring identification
G Gosztolya, R Busa-Fekete, T Grósz, L Tóth
International Speech Communication Association (ISCA), 2017
Detecting mild cognitive impairment by exploiting linguistic information from transcripts
V Vincze, G Gosztolya, L Tóth, I Hoffmann, G Szatlóczki, Z Bánréti, ...
Proceedings of the 54th Annual Meeting of the Association for Computational …, 2016
On naive Bayes in speech recognition
L Toth, A Kocsor, J Csirik
Zielona Góra: Uniwersytet Zielonogórski, 2005
Convolutional deep rectifier neural nets for phone recognition
L Tóth
Interspeech, 2013
Multi-Task Learning of Speech Recognition and Speech Synthesis Parameters for Ultrasound-based Silent Speech Interfaces.
L Tóth, G Gosztolya, T Grósz, A Markó, TG Csapó
INTERSPEECH, 3172-3176, 2018
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