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Tamás Grósz
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2020 – today
- 2024
- [j9]Georgios Karakasidis
, Mikko Kurimo, Peter Bell, Tamás Grósz
Comparison and analysis of new curriculum criteria for end-to-end ASR. Speech Commun. 163: 103113 (2024) - [j8]Aku Rouhe
Principled Comparisons for End-to-End Speech Recognition: Attention vs Hybrid at the 1000-Hour Scale. IEEE ACM Trans. Audio Speech Lang. Process. 32: 623-638 (2024) - [j7]Dejan Porjazovski
From Raw Speech to Fixed Representations: A Comprehensive Evaluation of Speech Embedding Techniques. IEEE ACM Trans. Audio Speech Lang. Process. 32: 3546-3560 (2024) - [c42]Anne Marte Haug Olstad, Anna Smolander, Sofia Strömbergsson, Sari Ylinen, Minna Lehtonen, Mikko Kurimo, Yaroslav Getman, Tamás Grósz, Xinwei Cao, Torbjørn Svendsen, Giampiero Salvi:
Collecting Linguistic Resources for Assessing Children's Pronunciation of Nordic Languages. LREC/COLING 2024: 3529-3537 - [c41]Anja Virkkunen, Marek Sarvas, Guangpu Huang, Tamás Grósz
Investigating the Clusters Discovered By Pre-Trained AV-HuBERT. ICASSP 2024: 11196-11200 - [c40]Mehedi Hasan Bijoy
Multimodal Humor Detection and Social Perception Prediction. MuSe@ACM Multimedia 2024: 60-64 - 2023
- [j6]Yaroslav Getman
Developing an AI-Assisted Low-Resource Spoken Language Learning App for Children. IEEE Access 11: 86025-86037 (2023) - [j5]Anssi Moisio
Lahjoita puhetta: a large-scale corpus of spoken Finnish with some benchmarks. Lang. Resour. Evaluation 57(3): 1295-1327 (2023) - [c39]Dejan Porjazovski, Tamás Grósz
Topic Identification for Spontaneous Speech: Enriching Audio Features with Embedded Linguistic Information. EUSIPCO 2023: 396-400 - [c38]Tamás Grósz
Investigating wav2vec2 context representations and the effects of fine-tuning, a case-study of a Finnish model. INTERSPEECH 2023: 196-200 - [c37]Dejan Porjazovski
Advancing Audio Emotion and Intent Recognition with Large Pre-Trained Models and Bayesian Inference. ACM Multimedia 2023: 9477-9481 - [c36]Tamás Grósz
Discovering Relevant Sub-spaces of BERT, Wav2Vec 2.0, ELECTRA and ViT Embeddings for Humor and Mimicked Emotion Recognition with Integrated Gradients. MuSe@ACM Multimedia 2023: 27-34 - [c35]Nhan Phan, Tamás Grósz, Mikko Kurimo:
CaptainA - A mobile app for practising Finnish pronunciation. NoDaLiDa 2023: 265-270 - [c34]Reima Karhila, Sari Ylinen
A pronunciation Scoring System Embedded into Children's Foreign Language Learning Games with Experimental Verification of Learning Benefits. SLaTE 2023: 21-25 - [c33]Yaroslav Getman, Ragheb Al-Ghezi, Tamás Grósz
Multi-task wav2vec2 Serving as a Pronunciation Training System for Children. SLaTE 2023: 36-40 - [i10]Dejan Porjazovski, Tamás Grósz, Mikko Kurimo:
Topic Identification For Spontaneous Speech: Enriching Audio Features With Embedded Linguistic Information. CoRR abs/2307.11450 (2023) - [i9]Dejan Porjazovski, Yaroslav Getman, Tamás Grósz, Mikko Kurimo:
Advancing Audio Emotion and Intent Recognition with Large Pre-Trained Models and Bayesian Inference. CoRR abs/2310.10179 (2023) - 2022
- [c32]Tamás Grósz, Noora Kallioniemi, Harri Kiiskinen, Kimmo Laine, Anssi Moisio, Tommi Römpötti, Anja Virkkunen, Hannu Salmi, Mikko Kurimo, Jorma Laaksonen:
Tracing Signs of Urbanity in the Finnish Fiction Film of the 1950s: Toward a Multimodal Analysis of Audiovisual Data. DHNB 2022: 63-78 - [c31]Georgios Karakasidis, Tamás Grósz
Comparison and Analysis of New Curriculum Criteria for End-to-End ASR. INTERSPEECH 2022: 66-70 - [c30]Yaroslav Getman
wav2vec2-based Speech Rating System for Children with Speech Sound Disorder. INTERSPEECH 2022: 3618-3622 - [c29]Tamás Grósz
Wav2vec2-based Paralinguistic Systems to Recognise Vocalised Emotions and Stuttering. ACM Multimedia 2022: 7026-7029 - [i8]Anssi Moisio, Dejan Porjazovski, Aku Rouhe, Yaroslav Getman, Anja Virkkunen, Tamás Grósz, Krister Lindén, Mikko Kurimo:
Lahjoita puhetta - a large-scale corpus of spoken Finnish with some benchmarks. CoRR abs/2203.12906 (2022) - [i7]Georgios Karakasidis, Tamás Grósz, Mikko Kurimo:
Comparison and Analysis of New Curriculum Criteria for End-to-End ASR. CoRR abs/2208.05782 (2022) - [i6]Tamás Grósz, Mittul Singh, Sudarsana Reddy Kadiri, Hemant Kumar Kathania, Mikko Kurimo:
End-to-end Ensemble-based Feature Selection for Paralinguistics Tasks. CoRR abs/2210.15978 (2022) - 2021
- [c28]Tamás Grósz
LSTM-XL: Attention Enhanced Long-Term Memory for LSTM Cells. TDS 2021: 382-393 - 2020
- [j4]Rudolf Ferenc, Dénes Bán, Tamás Grósz, Tibor Gyimóthy:
Deep learning in static, metric-based bug prediction. Array 6: 100021 (2020) - [j3]Gábor Gosztolya
Social Signal Detection by Probabilistic Sampling DNN Training. IEEE Trans. Affect. Comput. 11(1): 164-177 (2020) - [c27]Hemant Kumar Kathania, Mittul Singh
Data Augmentation Using Prosody and False Starts to Recognize Non-Native Children's Speech. INTERSPEECH 2020: 260-264 - [c26]Tamás Grósz
Visual Interpretation of DNN-based Acoustic Models using Deep Autoencoders. MLVis@Eurographics/EuroVis 2020: 25-29 - [i5]Tamás Grósz, Mittul Singh, Sudarsana Reddy Kadiri, Hemant Kumar Kathania, Mikko Kurimo:
Aalto's End-to-End DNN systems for the INTERSPEECH 2020 Computational Paralinguistics Challenge. CoRR abs/2008.02689 (2020) - [i4]Hemant Kumar Kathania, Mittul Singh, Tamás Grósz, Mikko Kurimo:
Data augmentation using prosody and false starts to recognize non-native children's speech. CoRR abs/2008.12914 (2020)
2010 – 2019
- 2019
- [j2]László Varga
Automatic segmentation of hyperreflective foci in OCT images. Comput. Methods Programs Biomed. 178: 91-103 (2019) - [c25]Gergely Pap
A Reconstruction-Free Projection Selection Procedure for Binary Tomography Using Convolutional Neural Networks. ICIAR (1) 2019: 228-236 - [c24]Gábor Gosztolya, Ádám Pintér, László Tóth, Tamás Grósz
Autoencoder-Based Articulatory-to-Acoustic Mapping for Ultrasound Silent Speech Interfaces. IJCNN 2019: 1-8 - [c23]Tamás Gábor Csapó, Mohammed Salah Al-Radhi
Ultrasound-Based Silent Speech Interface Built on a Continuous Vocoder. INTERSPEECH 2019: 894-898 - [p1]György Kovács, Tamás Grósz, Tamás Váradi:
Using Deep Rectifier Neural Nets and Probabilistic Sampling for Topical Unit Classification. Cognitive Infocommunications, Theory and Applications 2019: 1-24 - [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
- [b1]Tamás Grósz:
Training Methods for Deep Neural Network-Based Acoustic Models in Speech Recognition. University of Szeged, Hungary, 2018 - [j1]Péter Bodnár, Tamás Grósz
Efficient visual code localization with neural networks. Pattern Anal. Appl. 21(1): 249-260 (2018) - [c22]Tamás Grósz
F0 Estimation for DNN-Based Ultrasound Silent Speech Interfaces. ICASSP 2018: 291-295 - [c21]Melinda Katona, Attila Kovács, László Varga
Automatic Detection and Characterization of Biomarkers in OCT Images. ICIAR 2018: 706-714 - [c20]Gábor Gosztolya, Tamás Grósz
General Utterance-Level Feature Extraction for Classifying Crying Sounds, Atypical & Self-Assessed Affect and Heart Beats. INTERSPEECH 2018: 531-535 - [c19]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 - 2017
- [c18]Tamás Grósz
Training Context-Dependent DNN Acoustic Models Using Probabilistic Sampling. INTERSPEECH 2017: 1621-1625 - [c17]Tamás Grósz
A Comparative Evaluation of GMM-Free State Tying Methods for ASR. INTERSPEECH 2017: 1626-1630 - [c16]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 - [c15]Tamás Gábor Csapó
DNN-Based Ultrasound-to-Speech Conversion for a Silent Speech Interface. INTERSPEECH 2017: 3672-3676 - 2016
- [c14]György Kovács, Tamás Grósz
Topical unit classification using deep neural nets and probabilistic sampling. CogInfoCom 2016: 199-204 - [c13]Gábor Gosztolya, László Tóth
Detecting Mild Cognitive Impairment from Spontaneous Speech by Correlation-Based Phonetic Feature Selection. INTERSPEECH 2016: 107-111 - [c12]Gábor Gosztolya, Tamás Grósz
Estimating the Sincerity of Apologies in Speech by DNN Rank Learning and Prosodic Analysis. INTERSPEECH 2016: 2026-2030 - [c11]Gábor Gosztolya, Tamás Grósz
Determining Native Language and Deception Using Phonetic Features and Classifier Combination. INTERSPEECH 2016: 2418-2422 - [c10]Gábor Gosztolya, Tamás Grósz
GMM-Free Flat Start Sequence-Discriminative DNN Training. INTERSPEECH 2016: 3409-3413 - [i1]Gábor Gosztolya, Tamás Grósz, László Tóth:
GMM-Free Flat Start Sequence-Discriminative DNN Training. CoRR abs/1610.03256 (2016) - 2015
- [c9]Gábor Gosztolya, Tamás Grósz
Building context-dependent DNN acoustic models using Kullback-Leibler divergence-based state tying. ICASSP 2015: 4570-4574 - [c8]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 - 2014
- [c7]Péter Bodnár, Tamás Grósz, László Tóth, László G. Nyúl:
Localization of Visual Codes in the DCT Domain Using Deep Rectifier Neural Networks. ANNIIP 2014: 37-44 - [c6]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 - [c5]Tamás Grósz
QR code localization using deep neural networks. MLSP 2014: 1-6 - [c4]Tamás Grósz, Gábor Gosztolya, László Tóth:
A Sequence Training Method for Deep Rectifier Neural Networks in Speech Recognition. SPECOM 2014: 81-88 - [c3]György Kovács, László Tóth, Tamás Grósz:
Robust Multi-Band ASR Using Deep Neural Nets and Spectro-temporal Features. SPECOM 2014: 386-393 - [c2]Tamás Grósz
Document Classification with Deep Rectifier Neural Networks and Probabilistic Sampling. TSD 2014: 108-115 - 2013
- [c1]László Tóth
A Comparison of Deep Neural Network Training Methods for Large Vocabulary Speech Recognition. TSD 2013: 36-43
Coauthor Index
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last updated on 2024-12-02 22:26 CET by the dblp team
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