The COST 278 MASPER Initiative - Crosslingual Speech Recognition with Large Telephone Databases. - Andrej Zgank; Zdravko Kacic; Frank Diehl; Klára Vicsi; György Szaszák; Jozef Juhár; Slavomír Lihan (LREC, 2004)

Examination of Pronunciation Variation from Hand-Labelled Corpora. - György Szaszák; Klára Vicsi (TSD, 2004)

Automatic Segmentation of Continuous Speech on Word Level Based on Supra-segmental Features. - Klára Vicsi; György Szaszák (Int. J. Speech Technol., 2005)

Prosodic Cues for Automatic Phrase Boundary Detection in ASR. - Klára Vicsi; György Szaszák (TSD, 2006)

Using Prosody in Fixed Stress Languages for Improvement of Speech Recognition. - György Szaszák; Klára Vicsi (COST 2102 Workshop (Vietri), 2007)

Speech Recognition Supported by Prosodic Information for Fixed Stress Languages. - György Szaszák; Klára Vicsi (TSD, 2007)

Using prosody for the improvement of ASR - sentence modality recognition. - Klára Vicsi; György Szaszák (INTERSPEECH, 2008)

Automatic intonation classification for speech training systems. - György Szaszák; David Sztahó; Klára Vicsi (INTERSPEECH, 2009)

A szupraszegmentális jellemzők szerepe és felhasználása a gépi beszédfelismerésben - György Szaszák (2009)

Using prosody to improve automatic speech recognition. - Klára Vicsi; György Szaszák (Speech Commun., 2010)

Analysing the Correspondence Between Automatic Prosodic Segmentation and Syntactic Structure. - György Szaszák; Katalin Nagy; András Beke (INTERSPEECH, 2011)

Automatic Intonation Recognition for the Prosodic Assessment of Language-Impaired Children. - Fabien Ringeval; Jean Demouy; György Szaszák; Mohamed Chetouani; L. Robel; Jean Xavier; David Cohen; Monique Plaza (IEEE Trans. Speech Audio Process., 2011)

Automatic prosodic and syntactic analysis from speech in cognitive infocommunication. - György Szaszák; András Beke (CogInfoCom, 2012)

Unsupervised Clustering of Prosodic Patterns in Spontaneous Speech. - András Beke; György Szaszák (TSD, 2012)

Exploiting Prosody for Syntactic Analysis in Automatic Speech Understanding. - György Szaszák; András Beke (J. Lang. Model., 2012)

Automatic phrase segmentation and clustering in spontaneous speech. - András Beke; György Szaszák; Viola Varadi (CogInfoCom, 2013)

Evaluating intra- and crosslingual adaptation for non-native speech recognition in a bilingual environment. - György Szaszák; Philip N. Garner (CogInfoCom, 2013)

Using phonological phrase segmentation to improve automatic keyword spotting for the highly agglutinating Hungarian language. - György Szaszák; András Beke (INTERSPEECH, 2013)

Combining NLP techniques and acoustic analysis for semantic focus detection in speech. - András Beke; György Szaszák (CogInfoCom, 2014)

Using automatic stress extraction from audio for improved prosody modelling in speech synthesis. - György Szaszák; András Beke; Gábor Olaszy; Bálint Pál Tóth (INTERSPEECH, 2015)

Automatic Close Captioning for Live Hungarian Television Broadcast Speech: A Fast and Resource-Efficient Approach. - Ádam Varga; Balázs Tarján; Zoltán Tobler; György Szaszák; Tibor Fegyó; Csaba Bordás; Péter Mihajlik (SPECOM, 2015)

Toward Exploring the Role of Disfluencies from an Acoustic Point of View: A New Aspect of (Dis)continuous Speech Prosody Modelling. - György Szaszák; András Beke (TSD, 2015)

Atom decomposition based stress detection and automatic phrasing of speech. - Máté Ákos Tündik; Branislav Gerazov; Aleksandar Gjoreski; György Szaszák (CogInfoCom, 2016)

Summarization of Spontaneous Speech using Automatic Speech Recognition and a Speech Prosody based Tokenizer. - György Szaszák; Máté Ákos Tündik; András Beke (KDIR, 2016)

Estimating the Sincerity of Apologies in Speech by DNN Rank Learning and Prosodic Analysis. - Gábor Gosztolya; Tamás Grósz; György Szaszák; László Tóth 001 (INTERSPEECH, 2016)

Automatic Summarization of Highly Spontaneous Speech. - András Beke; György Szaszák (SPECOM, 2016)

Design of a Speech Corpus for Research on Cross-Lingual Prosody Transfer. - Milan Secujski; Branislav Gerazov; Tamás Gábor Csapó; Vlado Delic; Philip N. Garner; Aleksandar Gjoreski; David Guennec; Zoran A. Ivanovski; Aleksandar Melov; Géza Németh; Ana Stojkovic; György Szaszák (SPECOM, 2016)

Combining Atom Decomposition of the F0 Track and HMM-based Phonological Phrase Modelling for Robust Stress Detection in Speech. - György Szaszák; Máté Ákos Tündik; Branislav Gerazov; Aleksandar Gjoreski (SPECOM, 2016)

Ensemble Deep Neural Network Based Waveform-Driven Stress Model for Speech Synthesis. - Bálint Pál Tóth; Kornél István Kis; György Szaszák; Géza Németh (SPECOM, 2016)

A context-aware speech recognition and understanding system for air traffic control domain. - Youssef Oualil; Dietrich Klakow; György Szaszák; Ajay Srinivasamurthy; Hartmut Helmke; Petr Motlícek (ASRU, 2017)

A prosody inspired RNN approach for punctuation of machine produced speech transcripts to improve human readability. - Anna Moró; György Szaszák (CogInfoCom, 2017)

Assessment of pathological speech prosody based on automatic stress detection and phrasing approaches. - Máté Ákos Tündik; Gábor Kiss; David Sztahó; György Szaszák (CogInfoCom, 2017)

Á bilingual comparison of MaxEnt-and RNN-based punctuation restoration in speech transcripts. - Máté Ákos Tündik; Balázs Tarján; György Szaszák (CogInfoCom, 2017)

A Phonological Phrase Sequence Modelling Approach for Resource Efficient and Robust Real-Time Punctuation Recovery. - Anna Moró; György Szaszák (INTERSPEECH, 2017)

Semi-Supervised Learning with Semantic Knowledge Extraction for Improved Speech Recognition in Air Traffic Control. - Ajay Srinivasamurthy; Petr Motlícek; Ivan Himawan; György Szaszák; Youssef Oualil; Hartmut Helmke (INTERSPEECH, 2017)

Low Latency MaxEnt- and RNN-Based Word Sequence Models for Punctuation Restoration of Closed Caption Data. - Máté Ákos Tündik; Balázs Tarján; György Szaszák (SLSP, 2017)

A semantic space approach for automatic summarization of documents. - Valér Kaszás; Máté Ákos Tündik; György Szaszák (CogInfoCom, 2018)

Joint Word- and Character-level Embedding CNN-RNN Models for Punctuation Restoration. - Máté Ákos Tündik; György Szaszák (CogInfoCom, 2018)

User-centric Evaluation of Automatic Punctuation in ASR Closed Captioning. - Máté Ákos Tündik; György Szaszák; Gábor Gosztolya; András Beke (INTERSPEECH, 2018)

Prosodic stress detection for fixed stress languages using formal atom decomposition and a statistical hidden Markov hybrid. - György Szaszák; Máté Ákos Tündik; Branislav Gerazov (Speech Commun., 2018)

N-gram Approximation of LSTM Recurrent Language Models for Single-pass Recognition of Hungarian Call Center Conversations. - Balázs Tarján; György Szaszák; Tibor Fegyó; Péter Mihajlik (CogInfoCom, 2019)

Artificial Neural Network and SVM based Voice Disorder Classification. - Miklós Gábriel Tulics; György Szaszák; Krisztina Mészáros; Klára Vicsi (CogInfoCom, 2019)

Leveraging a Character, Word and Prosody Triplet for an ASR Error Robust and Agglutination Friendly Punctuation Approach. - György Szaszák; Máté Ákos Tündik (INTERSPEECH, 2019)

Assessing the Semantic Space Bias Caused by ASR Error Propagation and its Effect on Spoken Document Summarization. - Máté Ákos Tündik; Valér Kaszás; György Szaszák (INTERSPEECH, 2019)

Investigating Sub-Word Embedding Strategies for the Morphologically Rich and Free Phrase-Order Hungarian. - Bálint Döbrössy; Márton Makrai; Balázs Tarján; György Szaszák (RepL4NLP@ACL, 2019)

Investigation on N-Gram Approximated RNNLMs for Recognition of Morphologically Rich Speech. - Balázs Tarján; György Szaszák; Tibor Fegyó; Péter Mihajlik (SLSP, 2019)

On the Effects of Automatic Transcription and Segmentation Errors in Hungarian Spoken Language Processing. - Máté Ákos Tündik; Valér Kaszás; György Szaszák (Period. Polytech. Electr. Eng. Comput. Sci., 2019)

Improving Real-time Recognition of Morphologically Rich Speech with Transformer Language Model. - Balázs Tarján; György Szaszák; Tibor Fegyó; Péter Mihajlik (CogInfoCom, 2020)

Using ASR Posterior Probability and Acoustic Features for Voice Disorder Classification. - Miklós Gábriel Tulics; György Szaszák; Krisztina Mészáros; Klára Vicsi (CogInfoCom, 2020)

On the Effectiveness of Neural Text Generation Based Data Augmentation for Recognition of Morphologically Rich Speech. - Balázs Tarján; György Szaszák; Tibor Fegyó; Péter Mihajlik (TDS, 2020)

Deep Transformer based Data Augmentation with Subword Units for Morphologically Rich Online ASR. - Balázs Tarján; György Szaszák; Tibor Fegyó; Péter Mihajlik (CoRR, 2020)

A low latency sequential model and its user-focused evaluation for automatic punctuation of ASR closed captions. - Máté Ákos Tündik; Balázs Tarján; György Szaszák (Comput. Speech Lang., 2020)

Deep Learning Methods in Speaker Recognition: A Review. - Dávid Sztahó; György Szaszák; András Beke (Period. Polytech. Electr. Eng. Comput. Sci., 2021)

Automatic Assessment Of Spoken English Proficiency Based on Multimodal and Multitask Transformers. - Kamel Nebhi; György Szaszák (RANLP, 2023)