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ORCIDLászló Tóth 0001
Person information
- affiliation: University of Szeged, Institute of Informatics, Szeged, Hungary
- affiliation: Hungarian Academy of Sciences and University of Szeged, MTA-SZTE Research Group on Artificial Intelligence, Szeged, Hungary
- not to be confused with: László Tóth 0002
Other persons with the same name
- László Tóth 0002 — University of Szeged, Department of Software Engineering, Szeged, Hungary
- László Tóth 0003 — University of Pécs, Hungary (and 1 more)
- László Tóth 0004 — University of Debrecen, Debrecen, Hungary
- László Tóth 0005 — Scansoft-Recognita, Inc.
- László Tóth 0006 — S. C. Neogen S. A., Tirgu Mures, Romania
- László Tóth 0007 — Budapest University of Technology and Economics, Budapest, Hungary
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2020 – today
- 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- [i14]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
- [j24]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) - [j23]José Vicente Egas López
, Réka Balogh, Nóra Imre, Ildikó Hoffmann, Martina Katalin Szabó, László Tóth, Magdolna Pákáski, János Kálmán, Gábor Gosztolya:
Automatic screening of mild cognitive impairment and Alzheimer's disease by means of posterior-thresholding hesitation representation. Comput. Speech Lang. 75: 101377 (2022) - [j22]Tamás Gábor Csapó, Gábor Gosztolya, László Tóth, Amin Honarmandi Shandiz, Alexandra Markó:
Optimizing the Ultrasound Tongue Image Representation for Residual Network-Based Articulatory-to-Acoustic Mapping. Sensors 22(22): 8601 (2022) - [c69]Gergely Pap, Krisztian Adam, Zoltan Gyorgypal, László Tóth, Zoltan Hegedus:
Depthwise Convolutions using Physicochemical Features of DNA for Transcription Factor Binding Site Classification: Physicochemical Features for DNA-Protein Classification with Depthwise Convolutions. ICAAI 2022: 15-21 - [c68]Mercedes Vetráb, José Vicente Egas López, Réka Balogh, Nóra Imre, Ildikó Hoffmann, László Tóth, Magdolna Pákáski, János Kálmán, Gábor Gosztolya:
Using Spectral Sequence-to-Sequence Autoencoders to Assess Mild Cognitive Impairment. ICASSP 2022: 6467-6471 - [c67]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 - [c66]Amin Honarmandi Shandiz, László Tóth:
Improved Processing of Ultrasound Tongue Videos by Combining ConvLSTM and 3D Convolutional Networks. IEA/AIE 2022: 265-274 - [i13]Amin Honarmandi Shandiz, László Tóth:
Improved Processing of Ultrasound Tongue Videos by Combining ConvLSTM and 3D Convolutional Networks. CoRR abs/2206.12947 (2022) - 2021
- [j21]Gábor Gosztolya, Réka Balogh, Nóra Imre, José Vicente Egas López, Ildikó Hoffmann, Veronika Vincze, László Tóth, Davangere P. Devanand, Magdolna Pákáski, János Kálmán:
Cross-lingual detection of mild cognitive impairment based on temporal parameters of spontaneous speech. Comput. Speech Lang. 69: 101215 (2021) - [c65]Amin Honarmandi Shandiz, László Tóth, Gábor Gosztolya, Alexandra Markó, Tamás Gábor Csapó:
Improving Neural Silent Speech Interface Models by Adversarial Training. AICV 2021: 430-440 - [c64]Yide Yu, Amin Honarmandi Shandiz, László Tóth:
Reconstructing Speech from Real-Time Articulatory MRI Using Neural Vocoders. EUSIPCO 2021: 945-949 - [c63]José Vicente Egas López, Mercedes Vetráb, László Tóth, Gábor Gosztolya:
Identifying Conflict Escalation and Primates by Using Ensemble X-Vectors and Fisher Vector Features. Interspeech 2021: 476-480 - [c62]Amin Honarmandi Shandiz, László Tóth, Gábor Gosztolya, Alexandra Markó, Tamás Gábor Csapó:
Neural Speaker Embeddings for Ultrasound-Based Silent Speech Interfaces. Interspeech 2021: 1932-1936 - [c61]Amin Honarmandi Shandiz, László Tóth:
Voice Activity Detection for Ultrasound-Based Silent Speech Interfaces Using Convolutional Neural Networks. TDS 2021: 499-510 - [i12]László Tóth, Amin Honarmandi Shandiz:
3D Convolutional Neural Networks for Ultrasound-Based Silent Speech Interfaces. CoRR abs/2104.11532 (2021) - [i11]Yide Yu, Amin Honarmandi Shandiz, László Tóth:
Reconstructing Speech from Real-Time Articulatory MRI Using Neural Vocoders. CoRR abs/2104.11598 (2021) - [i10]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) - [i9]Amin Honarmandi Shandiz, László Tóth:
Voice Activity Detection for Ultrasound-based Silent Speech Interfaces using Convolutional Neural Networks. CoRR abs/2105.13718 (2021) - [i8]Amin Honarmandi Shandiz, László Tóth, Gábor Gosztolya, Alexandra Markó, Tamás Gábor Csapó:
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, Gábor Gosztolya, Alexandra Markó, Géza Németh, Tamás Gábor Csapó:
Adaptation of Tacotron2-based Text-To-Speech for Articulatory-to-Acoustic Mapping using Ultrasound Tongue Imaging. CoRR abs/2107.12051 (2021) - 2020
- [j20]Gábor Gosztolya, Tamás Grósz, László Tóth:
Social Signal Detection by Probabilistic Sampling DNN Training. IEEE Trans. Affect. Comput. 11(1): 164-177 (2020) - [c60]László Tóth, Amin Honarmandi Shandiz:
3D Convolutional Neural Networks for Ultrasound-Based Silent Speech Interfaces. ICAISC (1) 2020: 159-169 - [c59]László Tóth, Balázs Nagy, Tibor Gyimóthy, László Vidács:
Mining Hypernyms Semantic Relations from Stack Overflow. ICSE (Workshops) 2020: 360-366 - [c58]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 - [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
- [j19]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) - [c57]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 - [c56]Gábor Gosztolya, Ádám Pintér, László Tóth, Tamás Grósz, Alexandra Markó, Tamás Gábor Csapó:
Autoencoder-Based Articulatory-to-Acoustic Mapping for Ultrasound Silent Speech Interfaces. IJCNN 2019: 1-8 - [c55]György Kovács, László Tóth, Dirk Van Compernolle, Marcus Liwicki:
Examining the Combination of Multi-Band Processing and Channel Dropout for Robust Speech Recognition. INTERSPEECH 2019: 421-425 - [c54]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 - [c53]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. INTERSPEECH 2019: 894-898 - [c52]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 - [c51]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
- [j18]Gábor Gosztolya, László Tóth:
A feature selection-based speaker clustering method for paralinguistic tasks. Pattern Anal. Appl. 21(1): 193-204 (2018) - [j17]Péter Bodnár, Tamás Grósz, László Tóth, László G. Nyúl:
Efficient visual code localization with neural networks. Pattern Anal. Appl. 21(1): 249-260 (2018) - [c50]Tamás Grósz, Gábor Gosztolya, László Tóth, Tamás Gábor Csapó, Alexandra Markó:
F0 Estimation for DNN-Based Ultrasound Silent Speech Interfaces. ICASSP 2018: 291-295 - [c49]Gábor Gosztolya, Tamás Grósz, László Tóth:
General Utterance-Level Feature Extraction for Classifying Crying Sounds, Atypical & Self-Assessed Affect and Heart Beats. INTERSPEECH 2018: 531-535 - [c48]László Tóth, Gábor Gosztolya, Tamás Grósz, Alexandra Markó, Tamás Gábor Csapó:
Multi-Task Learning of Speech Recognition and Speech Synthesis Parameters for Ultrasound-based Silent Speech Interfaces. INTERSPEECH 2018: 3172-3176 - [c47]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 - [c46]László Tóth, György Kovács, Dirk Van Compernolle:
A Perceptually Inspired Data Augmentation Method for Noise Robust CNN Acoustic Models. SPECOM 2018: 697-706 - 2017
- [j16]György Kovács, László Tóth, Dirk Van Compernolle, Sriram Ganapathy:
Increasing the robustness of CNN acoustic models using autoregressive moving average spectrogram features and channel dropout. Pattern Recognit. Lett. 100: 44-50 (2017) - [j15]Gábor Gosztolya, László Tóth:
DNN-Based Feature Extraction for Conflict Intensity Estimation From Speech. IEEE Signal Process. Lett. 24(12): 1837-1841 (2017) - [c45]Tamás Grósz, Gábor Gosztolya, László Tóth:
Training Context-Dependent DNN Acoustic Models Using Probabilistic Sampling. INTERSPEECH 2017: 1621-1625 - [c44]Tamás Grósz, Gábor Gosztolya, László Tóth:
A Comparative Evaluation of GMM-Free State Tying Methods for ASR. INTERSPEECH 2017: 1626-1630 - [c43]Gábor Gosztolya, Róbert Busa-Fekete, Tamás Grósz, László Tóth:
DNN-Based Feature Extraction and Classifier Combination for Child-Directed Speech, Cold and Snoring Identification. INTERSPEECH 2017: 3522-3526 - [c42]Tamás Gábor Csapó, Tamás Grósz, Gábor Gosztolya, László Tóth, Alexandra Markó:
DNN-Based Ultrasound-to-Speech Conversion for a Silent Speech Interface. INTERSPEECH 2017: 3672-3676 - [c41]László Tóth:
Multi-resolution spectral input for convolutional neural network-based speech recognition. SpeD 2017: 1-6 - 2016
- [c40]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 - [c39]Gábor Gosztolya, László Tóth, Tamás Grósz, Veronika Vincze, Ildikó Hoffmann, Gréta Szatlóczki, Magdolna Pákáski, János Kálmán:
Detecting Mild Cognitive Impairment from Spontaneous Speech by Correlation-Based Phonetic Feature Selection. INTERSPEECH 2016: 107-111 - [c38]Gábor Gosztolya, Tamás Grósz, György Szaszák, László Tóth:
Estimating the Sincerity of Apologies in Speech by DNN Rank Learning and Prosodic Analysis. INTERSPEECH 2016: 2026-2030 - [c37]Gábor Gosztolya, Tamás Grósz, Róbert Busa-Fekete, László Tóth:
Determining Native Language and Deception Using Phonetic Features and Classifier Combination. INTERSPEECH 2016: 2418-2422 - [c36]Gábor Gosztolya, Tamás Grósz, László Tóth:
GMM-Free Flat Start Sequence-Discriminative DNN Training. INTERSPEECH 2016: 3409-3413 - [c35]László Tóth, Gábor Gosztolya:
Adaptation of DNN Acoustic Models Using KL-divergence Regularization and Multi-task Training. SPECOM 2016: 108-115 - [i1]Gábor Gosztolya, Tamás Grósz, László Tóth:
GMM-Free Flat Start Sequence-Discriminative DNN Training. CoRR abs/1610.03256 (2016) - 2015
- [j14]György Kovács, László Tóth:
Joint Optimization of Spectro-Temporal Features and Deep Neural Nets for Robust Automatic Speech Recognition. Acta Cybern. 22(1): 117-134 (2015) - [j13]László Tóth:
Phone recognition with hierarchical convolutional deep maxout networks. EURASIP J. Audio Speech Music. Process. 2015: 25 (2015) - [j12]György Kovács, László Tóth, Dirk Van Compernolle:
Selection and enhancement of Gabor filters for automatic speech recognition. Int. J. Speech Technol. 18(1): 1-16 (2015) - [c34]Gábor Gosztolya, Tamás Grósz, László Tóth, David Imseng:
Building context-dependent DNN acoustic models using Kullback-Leibler divergence-based state tying. ICASSP 2015: 4570-4574 - [c33]László Tóth:
Modeling long temporal contexts in convolutional neural network-based phone recognition. ICASSP 2015: 4575-4579 - [c32]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 - [c31]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
- [c30]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 - [c29]László Tóth:
Combining time- and frequency-domain convolution in convolutional neural network-based phone recognition. ICASSP 2014: 190-194 - [c28]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 - [c27]László Tóth:
Convolutional deep maxout networks for phone recognition. INTERSPEECH 2014: 1078-1082 - [c26]Tamás Grósz, Péter Bodnár, László Tóth, László G. Nyúl:
QR code localization using deep neural networks. MLSP 2014: 1-6 - [c25]Tamás Grósz, Gábor Gosztolya, László Tóth:
A Sequence Training Method for Deep Rectifier Neural Networks in Speech Recognition. SPECOM 2014: 81-88 - [c24]György Kovács, László Tóth, Tamás Grósz:
Robust Multi-Band ASR Using Deep Neural Nets and Spectro-temporal Features. SPECOM 2014: 386-393 - 2013
- [c23]László Tóth:
Phone recognition with deep sparse rectifier neural networks. ICASSP 2013: 6985-6989 - [c22]Gábor Gosztolya, Róbert Busa-Fekete, László Tóth:
Detecting autism, emotions and social signals using adaboost. INTERSPEECH 2013: 220-224 - [c21]László Tóth:
Convolutional deep rectifier neural nets for phone recognition. INTERSPEECH 2013: 1722-1726 - [c20]László Tóth, Tamás Grósz:
A Comparison of Deep Neural Network Training Methods for Large Vocabulary Speech Recognition. TSD 2013: 36-43 - [c19]György Kovács, László Tóth:
The Joint Optimization of Spectro-Temporal Features and Neural Net Classifiers. TSD 2013: 552-559 - 2011
- [c18]László Tóth:
A hierarchical, context-dependent neural network architecture for improved phone recognition. ICASSP 2011: 5040-5043 - [c17]Gábor Gosztolya, György Kovács, László Tóth:
Spoken term detection from noisy input. SACI 2011: 91-96 - [c16]György Kovács, László Tóth:
Phone recognition experiments with 2D-DCT spectro-temporal features. SACI 2011: 143-146 - 2010
- [j11]László Tóth, Balázs Tarján, Gellért Sárosi, Péter Mihajlik:
Speech Recognition Experiments with Audiobooks. Acta Cybern. 19(4): 695-713 (2010)
2000 – 2009
- 2009
- [c15]Gábor Gosztolya, András Bánhalmi, László Tóth:
Using One-Class Classification Techniques in the Anti-phoneme Problem. IbPRIA 2009: 433-440 - 2008
- [c14]Gábor Gosztolya, László Tóth:
Detection of Phoneme Boundaries Using Spiking Neurons. ICAISC 2008: 782-793 - [c13]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 - 2007
- [j10]László Tóth, András Kocsor:
A segment-based interpretation of HMM/ANN hybrids. Comput. Speech Lang. 21(3): 562-578 (2007) - [j9]András Bánhalmi, Dénes Paczolay, László Tóth, András Kocsor:
Development of a Hungarian Medical Dictation System. Informatica (Slovenia) 31(2): 241-246 (2007) - [c12]László Tóth:
Benchmarking human performance on the acoustic and linguistic subtasks of ASR systems. INTERSPEECH 2007: 382-385 - 2006
- [j8]András Bánhalmi, Dénes Paczolay, László Tóth, András Kocsor:
Investigating the robustness of a Hungarian medical dictation system under various conditions. Int. J. Speech Technol. 9(3-4): 121-131 (2006) - 2005
- [c11]László Tóth, András Kocsor:
Training HMM/ANN Hybrid Speech Recognizers by Probabilistic Sampling. ICANN (1) 2005: 597-603 - [c10]András Bánhalmi, Kornél Kovács, András Kocsor, László Tóth:
Fundamental frequency estimation by least-squares harmonic model fitting. INTERSPEECH 2005: 305-308 - [c9]László Tóth, András Kocsor:
Explicit Duration Modelling in HMM/ANN Hybrids. TSD 2005: 310-317 - 2004
- [j7]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) - [j6]Gyula Zsigri, András Kocsor, László Tóth, Györgyi Sejtes:
Phonetic Level Annotation and Segmentation of Hungarian Speech Databases. Acta Cybern. 16(4): 659-673 (2004) - [j5]András Kocsor, László Tóth:
Application of Kernel-Based Feature Space Transformations and Learning Methods to Phoneme Classification. Appl. Intell. 21(2): 129-142 (2004) - [j4]András Kocsor, László Tóth:
Kernel-based feature extraction with a speech technology application. IEEE Trans. Signal Process. 52(8): 2250-2263 (2004) - [c8]László Tóth, Gábor Gosztolya:
Replicator Neural Networks for Outlier Modeling in Segmental Speech Recognition. ISNN (1) 2004: 996-1001 - 2003
- [j3]Gábor Gosztolya, András Kocsor, László Tóth:
Various Robust Search Methods in a Hungarian Speech Recognition System. Acta Cybern. 16(2): 229-240 (2003) - [c7]László Tóth, András Kocsor:
Harmonic alternatives to sine-wave speech. INTERSPEECH 2003: 2073-2076 - [c6]Dénes Paczolay, András Kocsor, László Tóth:
Real-Time Vocal Tract Length Normalization. TSD 2003: 309-314 - 2002
- [c5]Kornél Kovács, András Kocsor, László Tóth:
Hungarian Speech Synthesis Using a Phase Exact HNM Approach. SOFSEM 2002: 181-185 - 2001
- [c4]András Kocsor, László Tóth, László Felföldi:
Application of Feature Transformation and Learning Methods in Phoneme Classification. IEA/AIE 2001: 502-512 - [c3]András Kocsor, László Tóth, Dénes Paczolay:
A Nonlinearized Discriminant Analysis and Its Application to Speech Impediment Therapy. TSD 2001: 249-257 - 2000
- [j2]András Kocsor, László Tóth, András Kuba, Kornél Kovács, Márk Jelasity, Tibor Gyimóthy, János Csirik:
A Comparative Study of Several Feature Transformation and Learning Methods for Phoneme Classification. Int. J. Speech Technol. 3(3-4): 263-276 (2000) - [c2]László Tóth, András Kocsor, Kornél Kovács:
A Discriminative Segmental Speech Model and Its Application to Hungarian Number Recognition. TSD 2000: 307-313
1990 – 1999
- 1999
- [j1]András Kocsor, László Tóth, I. Bálint:
Optimal Parameters of a Sinusoidal Representation of Signals. Acta Cybern. 14(2): 315-330 (1999) - 1997
- [c1]Zoltán Alexin, János Csirik, Tibor Gyimóthy, Márk Jelasity, László Tóth:
Learning Phonetic Rules in a Speech Recognition System. ILP 1997: 37-44
Coauthor Index
[c70] [i14] [j24] [j23] [j22] [c68] [c67] [j21] [c65] [c63] [c62] [i10] [i8] [i7] [i6] [j20] [c58] [i5] [i4] [j19] [c57] [c56] [c54] [c53] [c52] [c51] [i3] [i2] [j18] [c50] [c49] [c48] [c47] [j15] [c45] [c44] [c43] [c42] [c40] [c39] [c38] [c37] [c36] [c35] [i1] [c34] [c32] [c31] [c28] [c25] [c22] [c17] [c15] [c14] [c13] [j7] [c8] [j3]
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Citation data
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load citations from opencitations.net
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OpenAlex data
Load additional information about publications from 
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last updated on 2024-06-17 02:21 CEST by the dblp team
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