| Deep learning methods in speaker recognition: a review D Sztahó, G Szaszák, A Beke arXiv preprint arXiv:1911.06615, 2019 | 97 | 2019 |
| Using prosody to improve automatic speech recognition K Vicsi, G Szaszák Speech Communication 52 (5), 413-426, 2010 | 81 | 2010 |
| Automatic intonation recognition for the prosodic assessment of language-impaired children F Ringeval, J Demouy, G Szaszak, M Chetouani, L Robel, J Xavier, ... IEEE Transactions on Audio, Speech, and Language Processing 19 (5), 1328-1342, 2010 | 76 | 2010 |
| The COST 278 MASPER Initiative-Crosslingual Speech Recognition with Large Telephone Databases. A Zgank, Z Kacic, F Diehl, K Vicsi, G Szaszák, J Juhár, S Lihan LREC-2004, 2107-2110, 2004 | 40 | 2004 |
| Automatic segmentation of continuous speech on word level based on supra-segmental features K Vicsi, G Szaszák International Journal of Speech Technology 8 (4), 363-370, 2005 | 37 | 2005 |
| A context-aware speech recognition and understanding system for air traffic control domain Y Oualil, D Klakow, G Szaszák, A Srinivasamurthy, H Helmke, P Motlicek 2017 IEEE automatic speech recognition and understanding workshop (ASRU …, 2017 | 33 | 2017 |
| Leveraging a Character, Word and Prosody Triplet for an ASR Error Robust and Agglutination Friendly Punctuation Approach G Szaszák, MA Tündik Proc. Interspeech 2019, 2988-2992, 2019 | 29 | 2019 |
| User-centric evaluation of automatic punctuation in ASR closed captioning MA Tündik, G Szaszák, G Gosztolya, A Beke International Speech Communication Association (ISCA), 2018 | 28 | 2018 |
| Automatic close captioning for live hungarian television broadcast speech: A fast and resource-efficient approach Á Varga, B Tarján, Z Tobler, G Szaszák, T Fegyó, C Bordás, P Mihajlik International Conference on Speech and Computer, 105-112, 2015 | 26 | 2015 |
| Exploiting prosody for automatic syntactic phrase boundary detection in speech G Szaszák, A Beke Journal of Language Modelling, 143–172-143–172, 2012 | 26 | 2012 |
| Joint word-and character-level embedding CNN-RNN models for punctuation restoration MÁ Tündik, G Szaszák 2018 9th IEEE International Conference on Cognitive Infocommunications …, 2018 | 25 | 2018 |
| Artificial neural network and svm based voice disorder classification MG Tulics, G Szaszák, K Mészáros, K Vicsi 2019 10th IEEE International Conference on Cognitive Infocommunications …, 2019 | 17 | 2019 |
| A Phonological Phrase Sequence Modelling Approach for Resource Efficient and Robust Real-Time Punctuation Recovery. A Moró, G Szaszák INTERSPEECH, 558-562, 2017 | 16 | 2017 |
| Estimating the Sincerity of Apologies in Speech by DNN Rank Learning and Prosodic Analysis G Gosztolya, T Grósz, G Szaszák, L Tóth INTERSPEECH, 2026-2030, 2016 | 16 | 2016 |
| Crosslingual transfer of source acoustic models to two different target languages A Zgank, Z Kacic, K Vicsi, G Szaszak, F Diehl, J Juhar, S Lihan Proc. Robust 2004, paper 19, 2004 | 14 | 2004 |
| Summarization of spontaneous speech using automatic speech recognition and a speech prosody based tokenizer G Szaszák, MÁ Tündik, A Beke International Conference on Knowledge Discovery and Information Retrieval 2 …, 2016 | 13 | 2016 |
| Automatic summarization of highly spontaneous speech A Beke, G Szaszák International Conference on Speech and Computer, 140-147, 2016 | 13 | 2016 |
| Unsupervised clustering of prosodic patterns in spontaneous speech A Beke, G Szaszák International Conference on Text, Speech and Dialogue, 648-655, 2012 | 13 | 2012 |
| Using prosody for the improvement of ASR-sentence modality recognition. K Vicsi, G Szaszák INTERSPEECH, 2877-2880, 2008 | 13 | 2008 |
| Investigating sub-word embedding strategies for the morphologically rich and free phrase-order Hungarian B Döbrössy, M Makrai, B Tarján, G Szaszák Proceedings of the 4th Workshop on Representation Learning for NLP (RepL4NLP …, 2019 | 12 | 2019 |
