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Gábor Gosztolya
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2020 – today
- 2024
- [c72]Gábor Gosztolya, András Bence Lázár, Ildikó Hoffmann, Otília Bagi, Fruzsina Fanni Farkas, Janka Gajdics, László Tóth, János Kálmán:
Automatic Assessment of Signs of Alcohol Dependency Syndrome from Spontaneous Speech. SPECOM (2) 2024: 18-29 - [c71]Gábor Gosztolya, László Tóth, Veronika Svindt, Judit Bóna, Ildikó Hoffmann:
Investigating the Utility of wav2vec 2.0 Hidden Layers for Detecting Multiple Sclerosis. SPECOM (1) 2024: 297-308 - 2023
- [j20]Mercedes Vetráb
, Gábor Gosztolya
Using Hybrid HMM/DNN Embedding Extractor Models in Computational Paralinguistic Tasks. Sensors 23(11): 5208 (2023) - [c70]László Tóth, Amin Honarmandi Shandiz, Gábor Gosztolya, Tamás Gábor Csapó:
Adaptation of Tongue Ultrasound-Based Silent Speech Interfaces Using Spatial Transformer Networks. INTERSPEECH 2023: 1169-1173 - [c69]José Vicente Egas López, Veronika Svindt, Judit Bóna, Ildikó Hoffmann, Gábor Gosztolya:
Automated Multiple Sclerosis Screening Based on Encoded Speech Representations. INTERSPEECH 2023: 3003-3007 - [c68]José Vicente Egas López, Gábor Gosztolya:
Using Custom X-vectors for the Automatic Screening of COVID-19 Based on Coughing Audio Samples. SACI 2023: 203-208 - [c67]Mercedes Vetráb
Aggregation Strategies of Wav2vec 2.0 Embeddings for Computational Paralinguistic Tasks. SPECOM (1) 2023: 79-93 - [c66]Ibrahim Ibrahimov
Data Augmentation Methods on Ultrasound Tongue Images for Articulation-to-Speech Synthesis. SSW 2023: 230-235 - [c65]José Vicente Egas López
Identifying Subjects Wearing a Mask from the Speech by Means of Encoded Speech Representations. TSD 2023: 131-140 - [i10]László Tóth, Amin Honarmandi Shandiz, Gábor Gosztolya, Tamás Gábor Csapó:
Adaptation of Tongue Ultrasound-Based Silent Speech Interfaces Using Spatial Transformer Networks. CoRR abs/2305.19130 (2023) - 2022
- [j19]Veronika Vincze, Martina Katalin Szabó, Ildikó Hoffmann, László Tóth, Magdolna Pákáski, János Kálmán, Gábor Gosztolya:
Linguistic Parameters of Spontaneous Speech for Identifying Mild Cognitive Impairment and Alzheimer Disease. Comput. Linguistics 48(1): 119-153 (2022) - [j18]José Vicente Egas López
Automatic screening of mild cognitive impairment and Alzheimer's disease by means of posterior-thresholding hesitation representation. Comput. Speech Lang. 75: 101377 (2022) - [j17]Gábor Gosztolya:
Optimizing class priors to improve the detection of social signals in audio data. Eng. Appl. Artif. Intell. 107: 104541 (2022) - [j16]Gábor Gosztolya
Estimating the degree of conflict in speech by employing Bag-of-Audio-Words and Fisher Vectors. Expert Syst. Appl. 205: 117613 (2022) - [j15]Tamás Gábor Csapó
Optimizing the Ultrasound Tongue Image Representation for Residual Network-Based Articulatory-to-Acoustic Mapping. Sensors 22(22): 8601 (2022) - [c64]Mercedes Vetráb
Using Spectral Sequence-to-Sequence Autoencoders to Assess Mild Cognitive Impairment. ICASSP 2022: 6467-6471 - [c63]Gábor Gosztolya, László Tóth, Veronika Svindt, Judit Bóna, Ildikó Hoffmann:
Using Acoustic Deep Neural Network Embeddings to Detect Multiple Sclerosis From Speech. ICASSP 2022: 6927-6931 - [c62]José Vicente Egas López, Gábor Kiss, Dávid Sztahó, Gábor Gosztolya:
Automatic Assessment of the Degree of Clinical Depression from Speech Using X-Vectors. ICASSP 2022: 8502-8506 - [c61]José Vicente Egas López, Gábor Gosztolya:
Identification of Subjects Wearing a Surgical Mask from Their Speech by Means of X-vectors and Fisher Vectors. MDAI 2022: 108-118 - [c60]José Vicente Egas López, Róbert Busa-Fekete, Gábor Gosztolya:
On the Use of Ensemble X-Vector Embeddings for Improved Sleepiness Detection. SPECOM 2022: 178-187 - 2021
- [j14]José Vicente Egas López
Using the Fisher Vector Approach for Cold Identification. Acta Cybern. 25(2): 223-232 (2021) - [j13]Gábor Gosztolya, Réka Balogh, Nóra Imre
Cross-lingual detection of mild cognitive impairment based on temporal parameters of spontaneous speech. Comput. Speech Lang. 69: 101215 (2021) - [j12]Gábor Gosztolya
Ensemble Bag-of-Audio-Words Representation Improves Paralinguistic Classification Accuracy. IEEE ACM Trans. Audio Speech Lang. Process. 29: 477-488 (2021) - [c59]Amin Honarmandi Shandiz
Improving Neural Silent Speech Interface Models by Adversarial Training. AICV 2021: 430-440 - [c58]José Vicente Egas López, Gábor Gosztolya:
Deep Neural Network Embeddings for the Estimation of the Degree of Sleepiness. ICASSP 2021: 7288-7292 - [c57]José Vicente Egas López, Mercedes Vetráb
Identifying Conflict Escalation and Primates by Using Ensemble X-Vectors and Fisher Vector Features. Interspeech 2021: 476-480 - [c56]Amin Honarmandi Shandiz
Neural Speaker Embeddings for Ultrasound-Based Silent Speech Interfaces. Interspeech 2021: 1932-1936 - [c55]Tamás Gábor Csapó, László Tóth, Gábor Gosztolya, Alexandra Markó:
Speech Synthesis from Text and Ultrasound Tongue Image-based Articulatory Input. SSW 2021: 31-36 - [c54]Csaba Zainkó, László Tóth, Amin Honarmandi Shandiz
Adaptation of Tacotron2-based Text-To-Speech for Articulatory-to-Acoustic Mapping using Ultrasound Tongue Imaging. SSW 2021: 54-59 - [i9]Amin Honarmandi Shandiz, László Tóth, Gábor Gosztolya, Alexandra Markó, Tamás Gábor Csapó:
Improving Neural Silent Speech Interface Models by Adversarial Training. CoRR abs/2104.11601 (2021) - [i8]Amin Honarmandi Shandiz
Neural Speaker Embeddings for Ultrasound-based Silent Speech Interfaces. CoRR abs/2106.04552 (2021) - [i7]Tamás Gábor Csapó, László Tóth, Gábor Gosztolya, Alexandra Markó:
Speech Synthesis from Text and Ultrasound Tongue Image-based Articulatory Input. CoRR abs/2107.02003 (2021) - [i6]Csaba Zainkó, László Tóth, Amin Honarmandi Shandiz
Adaptation of Tacotron2-based Text-To-Speech for Articulatory-to-Acoustic Mapping using Ultrasound Tongue Imaging. CoRR abs/2107.12051 (2021) - 2020
- [j11]Gábor Gosztolya
Social Signal Detection by Probabilistic Sampling DNN Training. IEEE Trans. Affect. Comput. 11(1): 164-177 (2020) - [c53]Tamás Gábor Csapó, Csaba Zainkó, László Tóth, Gábor Gosztolya, Alexandra Markó:
Ultrasound-Based Articulatory-to-Acoustic Mapping with WaveGlow Speech Synthesis. INTERSPEECH 2020: 2727-2731 - [c52]Gábor Gosztolya:
Very Short-Term Conflict Intensity Estimation Using Fisher Vectors. INTERSPEECH 2020: 3127-3131 - [c51]Gábor Gosztolya, Anita Bagi, Szilvia Szalóki, István Szendi, Ildikó Hoffmann:
Making a Distinction Between Schizophrenia and Bipolar Disorder Based on Temporal Parameters in Spontaneous Speech. INTERSPEECH 2020: 4566-4570 - [c50]José Vicente Egas López, Gábor Gosztolya:
Predicting a Cold from Speech Using Fisher Vectors; SVM and XGBoost as Classifiers. SPECOM 2020: 145-155 - [c49]Mercedes Vetráb
Investigating the Corpus Independence of the Bag-of-Audio-Words Approach. TDS 2020: 285-293 - [i5]Tamás Gábor Csapó, Csaba Zainkó, László Tóth, Gábor Gosztolya, Alexandra Markó:
Ultrasound-based Articulatory-to-Acoustic Mapping with WaveGlow Speech Synthesis. CoRR abs/2008.03152 (2020) - [i4]Gábor Gosztolya, László Tóth:
Applying Speech Tempo-Derived Features, BoAW and Fisher Vectors to Detect Elderly Emotion and Speech in Surgical Masks. CoRR abs/2008.03183 (2020)
2010 – 2019
- 2019
- [j10]Gábor Gosztolya, Veronika Vincze, László Tóth, Magdolna Pákáski, János Kálmán, Ildikó Hoffmann:
Identifying Mild Cognitive Impairment and mild Alzheimer's disease based on spontaneous speech using ASR and linguistic features. Comput. Speech Lang. 53: 181-197 (2019) - [j9]Gábor Gosztolya:
Posterior-thresholding feature extraction for paralinguistic speech classification. Knowl. Based Syst. 186 (2019) - [j8]Gábor Gosztolya
Calibrating AdaBoost for phoneme classification. Soft Comput. 23(1): 115-128 (2019) - [c48]Nóra Imre, Réka Balogh, Gábor Gosztolya, László Tóth, Tamás Várkonyi, Csaba Lengyel, Magdolna Pákáski, János Kálmán:
Automatic recognition of temporal speech features in type 2 diabetes mellitus with mild cognitive impairment. CogInfoCom 2019: 27-28 - [c47]Gábor Gosztolya, Ádám Pintér, László Tóth, Tamás Grósz
Autoencoder-Based Articulatory-to-Acoustic Mapping for Ultrasound Silent Speech Interfaces. IJCNN 2019: 1-8 - [c46]Gábor Gosztolya, László Tóth:
Calibrating DNN Posterior Probability Estimates of HMM/DNN Models to Improve Social Signal Detection from Audio Data. INTERSPEECH 2019: 515-519 - [c45]Tamás Gábor Csapó, Mohammed Salah Al-Radhi
Ultrasound-Based Silent Speech Interface Built on a Continuous Vocoder. INTERSPEECH 2019: 894-898 - [c44]Gábor Gosztolya:
Using Fisher Vector and Bag-of-Audio-Words Representations to Identify Styrian Dialects, Sleepiness, Baby & Orca Sounds. INTERSPEECH 2019: 2413-2417 - [c43]José Vicente Egas López, Juan Rafael Orozco-Arroyave, Gábor Gosztolya:
Assessing Parkinson's Disease from Speech Using Fisher Vectors. INTERSPEECH 2019: 3063-3067 - [c42]Gábor Gosztolya:
Using the Bag-of-Audio-Word Feature Representation of ASR DNN Posteriors for Paralinguistic Classification. INTERSPEECH 2019: 3940-3944 - [c41]Gábor Gosztolya, András Beke, Tilda Neuberger:
Differentiating Laughter Types via HMM/DNN and Probabilistic Sampling. SPECOM 2019: 122-132 - [c40]José Vicente Egas López, László Tóth, Ildikó Hoffmann, János Kálmán, Magdolna Pákáski, Gábor Gosztolya:
Assessing Alzheimer's Disease from Speech Using the i-vector Approach. SPECOM 2019: 289-298 - [c39]László Tóth, Gábor Gosztolya:
Reducing the Inter-speaker Variance of CNN Acoustic Models Using Unsupervised Adversarial Multi-task Training. SPECOM 2019: 481-490 - [i3]Gábor Gosztolya, Ádám Pintér, László Tóth, Tamás Grósz, Alexandra Markó, Tamás Gábor Csapó
Autoencoder-Based Articulatory-to-Acoustic Mapping for Ultrasound Silent Speech Interfaces. CoRR abs/1904.05259 (2019) - [i2]Tamás Gábor Csapó, Mohammed Salah Al-Radhi, Géza Németh, Gábor Gosztolya, Tamás Grósz, László Tóth, Alexandra Markó:
Ultrasound-based Silent Speech Interface Built on a Continuous Vocoder. CoRR abs/1906.09885 (2019) - 2018
- [j7]Gábor Gosztolya, László Tóth
A feature selection-based speaker clustering method for paralinguistic tasks. Pattern Anal. Appl. 21(1): 193-204 (2018) - [c38]Tamás Grósz
F0 Estimation for DNN-Based Ultrasound Silent Speech Interfaces. ICASSP 2018: 291-295 - [c37]Gábor Gosztolya, Tamás Grósz
General Utterance-Level Feature Extraction for Classifying Crying Sounds, Atypical & Self-Assessed Affect and Heart Beats. INTERSPEECH 2018: 531-535 - [c36]Máté Ákos Tündik, György Szaszák, Gábor Gosztolya, András Beke:
User-centric Evaluation of Automatic Punctuation in ASR Closed Captioning. INTERSPEECH 2018: 2628-2632 - [c35]László Tóth, Gábor Gosztolya, Tamás Grósz
Multi-Task Learning of Speech Recognition and Speech Synthesis Parameters for Ultrasound-based Silent Speech Interfaces. INTERSPEECH 2018: 3172-3176 - [c34]Gábor Gosztolya, Anita Bagi, Szilvia Szalóki, István Szendi, Ildikó Hoffmann:
Identifying Schizophrenia Based on Temporal Parameters in Spontaneous Speech. INTERSPEECH 2018: 3408-3412 - [c33]Gábor Gosztolya, Róbert Busa-Fekete:
Posterior Calibration for Multi-Class Paralinguistic Classification. SLT 2018: 119-125 - [c32]György Kovács, László Tóth, Gábor Gosztolya:
Multi-Band Processing With Gabor Filters and Time Delay Neural Nets for Noise Robust Speech Recognition. SLT 2018: 242-249 - 2017
- [j6]Gábor Gosztolya, László Tóth
DNN-Based Feature Extraction for Conflict Intensity Estimation From Speech. IEEE Signal Process. Lett. 24(12): 1837-1841 (2017) - [c31]Tamás Grósz
Training Context-Dependent DNN Acoustic Models Using Probabilistic Sampling. INTERSPEECH 2017: 1621-1625 - [c30]Tamás Grósz
A Comparative Evaluation of GMM-Free State Tying Methods for ASR. INTERSPEECH 2017: 1626-1630 - [c29]Gábor Gosztolya:
Optimized Time Series Filters for Detecting Laughter and Filler Events. INTERSPEECH 2017: 2376-2380 - [c28]Gábor Gosztolya, Róbert Busa-Fekete, Tamás Grósz
DNN-Based Feature Extraction and Classifier Combination for Child-Directed Speech, Cold and Snoring Identification. INTERSPEECH 2017: 3522-3526 - [c27]Tamás Gábor Csapó
DNN-Based Ultrasound-to-Speech Conversion for a Silent Speech Interface. INTERSPEECH 2017: 3672-3676 - 2016
- [c26]Veronika Vincze, Gábor Gosztolya, László Tóth, Ildikó Hoffmann, Gréta Szatlóczki, Zoltán Bánréti, Magdolna Pákáski, János Kálmán:
Detecting Mild Cognitive Impairment by Exploiting Linguistic Information from Transcripts. ACL (2) 2016 - [c25]Gábor Gosztolya, László Tóth
Detecting Mild Cognitive Impairment from Spontaneous Speech by Correlation-Based Phonetic Feature Selection. INTERSPEECH 2016: 107-111 - [c24]Gábor Gosztolya, Tamás Grósz
Estimating the Sincerity of Apologies in Speech by DNN Rank Learning and Prosodic Analysis. INTERSPEECH 2016: 2026-2030 - [c23]Gábor Gosztolya, Tamás Grósz
Determining Native Language and Deception Using Phonetic Features and Classifier Combination. INTERSPEECH 2016: 2418-2422 - [c22]Gábor Gosztolya, Tamás Grósz
GMM-Free Flat Start Sequence-Discriminative DNN Training. INTERSPEECH 2016: 3409-3413 - [c21]László Tóth
Adaptation of DNN Acoustic Models Using KL-divergence Regularization and Multi-task Training. SPECOM 2016: 108-115 - [c20]Gábor Gosztolya:
Detecting Laughter and Filler Events by Time Series Smoothing with Genetic Algorithms. SPECOM 2016: 232-239 - [i1]Gábor Gosztolya, Tamás Grósz, László Tóth:
GMM-Free Flat Start Sequence-Discriminative DNN Training. CoRR abs/1610.03256 (2016) - 2015
- [c19]Gábor Gosztolya, Tamás Grósz
Building context-dependent DNN acoustic models using Kullback-Leibler divergence-based state tying. ICASSP 2015: 4570-4574 - [c18]Tamás Grósz, Róbert Busa-Fekete, Gábor Gosztolya, László Tóth:
Assessing the degree of nativeness and parkinson's condition using Gaussian processes and deep rectifier neural networks. INTERSPEECH 2015: 919-923 - [c17]Gábor Gosztolya:
Conflict intensity estimation from speech using Greedy forward-backward feature selection. INTERSPEECH 2015: 1339-1343 - [c16]Gábor Gosztolya:
On evaluation metrics for social signal detection. INTERSPEECH 2015: 2504-2508 - [c15]László Tóth, Gábor Gosztolya, Veronika Vincze, Ildikó Hoffmann, Gréta Szatlóczki, Edit Biró, Fruzsina Zsura, Magdolna Pákáski, János Kálmán:
Automatic detection of mild cognitive impairment from spontaneous speech using ASR. INTERSPEECH 2015: 2694-2698 - 2014
- [c14]Gábor Gosztolya:
On the Concept of Correct Hits in Spoken Term Detection. AIC 2014: 75-85 - [c13]Gábor Gosztolya, Tamás Grósz, Róbert Busa-Fekete, László Tóth:
Detecting the intensity of cognitive and physical load using AdaBoost and deep rectifier neural networks. INTERSPEECH 2014: 452-456 - [c12]Gábor Gosztolya, József Dombi:
Applying Representative Uninorms for Phonetic Classifier Combination. MDAI 2014: 182-191 - [c11]Tamás Grósz, Gábor Gosztolya, László Tóth:
A Sequence Training Method for Deep Rectifier Neural Networks in Speech Recognition. SPECOM 2014: 81-88 - 2013
- [c10]Gábor Gosztolya, Róbert Busa-Fekete, László Tóth:
Detecting autism, emotions and social signals using adaboost. INTERSPEECH 2013: 220-224 - [c9]Gábor Gosztolya:
Using the Logarithmic Generator Function in the Spoken Term Detection Task. MDAI 2013: 94-104 - 2011
- [c8]Gábor Gosztolya, György Kovács, László Tóth
Spoken term detection from noisy input. SACI 2011: 91-96 - 2010
- [b1]Gábor Gosztolya:
Improving speed and accuracy in automatic speech recognition. University of Szeged, Hungary, 2010
2000 – 2009
- 2009
- [j5]Gábor Gosztolya, József Dombi, András Kocsor:
Applying the Generalized Dombi Operator Family to the Speech Recognition Task. J. Comput. Inf. Technol. 17(3): 285-293 (2009) - [c7]Gábor Gosztolya, András Bánhalmi, László Tóth
Using One-Class Classification Techniques in the Anti-phoneme Problem. IbPRIA 2009: 433-440 - 2008
- [c6]Gábor Gosztolya, László Tóth
Detection of Phoneme Boundaries Using Spiking Neurons. ICAISC 2008: 782-793 - [c5]László Tóth, Joe Frankel, Gábor Gosztolya, Simon King:
Cross-lingual portability of MLP-based tandem features - a case study for English and Hungarian. INTERSPEECH 2008: 2695-2698 - 2006
- [j4]Gábor Gosztolya, András Kocsor:
A Hierarchical Evaluation Methodology in Speech Recognition. Acta Cybern. 17(2): 213-224 (2006) - [j3]András Kocsor, Gábor Gosztolya:
The use of speed-up techniques for a speech recognizer system. Int. J. Speech Technol. 9(3-4): 95-107 (2006) - 2005
- [c4]Gábor Gosztolya, András Kocsor:
Speeding Up Dynamic Search Methods in Speech Recognition. IEA/AIE 2005: 98-100 - 2004
- [j2]László Tóth, András Kocsor, Gábor Gosztolya:
Telephone Speech Recognition via the Combination of Knowledge Sources in a Segmental Speech Model. Acta Cybern. 16(4): 643-657 (2004) - [c3]László Tóth, Gábor Gosztolya:
Replicator Neural Networks for Outlier Modeling in Segmental Speech Recognition. ISNN (1) 2004: 996-1001 - [c2]Gábor Gosztolya, András Kocsor:
Aggregation Operators and Hypothesis Space Reductions in Speech Recognition. TSD 2004: 315-322 - 2003
- [j1]Gábor Gosztolya, András Kocsor, László Tóth:
Various Robust Search Methods in a Hungarian Speech Recognition System. Acta Cybern. 16(2): 229-240 (2003) - [c1]Gábor Gosztolya, András Kocsor:
Improving the Multi-stack Decoding Algorithm in a Segment-Based Speech Recognizer. IEA/AIE 2003: 744-749
Coauthor Index
[c72] [c71] [c70] [i10] [j19] [j18] [j15] [c64] [c63] [j13] [c59] [c57] [c56] [c55] [c54] [i9] [i8] [i7] [i6] [j11] [c53] [i5] [i4] [j10] [c48] [c47] [c46] [c45] [c40] [c39] [i3] [i2] [j7] [c38] [c37] [c35] [c32] [j6] [c31] [c30] [c28] [c27] [c26] [c25] [c24] [c23] [c22] [c21] [i1] [c19] [c18] [c15] [c13] [c11] [c10] [c8] [c7] [c6] [c5] [j2] [c3] [j1]
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