Kocsor A, Tóth L, Felföldi L.  2001.  Application of Feature Transformation and Learning Methods in Phoneme Classification. Engineering of Intelligent Systems : 14th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2001, LNAI vol. 2070. :502-512.

Gosztolya G, Grósz T, Tóth L, Markó A, Csapó TGábor.  2020.  Applying DNN Adaptation to Reduce the Session Dependency of Ultrasound Tongue Imaging-based Silent Speech Interfaces. Acta Polytechnica Hungarica. 17:109–124.

Gosztolya G, Pintér Á, Tóth L, Grósz T, Markó A, Csapó TGábor.  2019.  Autoencoder-Based Articulatory-to-Acoustic Mapping for Ultrasound Silent Speech Interfaces. Proceedings of IJCNN.

Gosztolya G, Tóth L.  2019.  Calibrating DNN Posterior Probability Estimates of HMM/DNN Models to Improve Social Signal Detection From Audio Data. Proceedings of Interspeech. :515–519.

Felföldi L, Kocsor A, Tóth L.  2002.  Classifier Combination in Speech Recognition. Conference of PhD students on Computer Sciences, Volume of Extended Abstracts. :30.

Kocsor A, Tóth L, Kuba, Jr. A, Kovács K, Jelasity M, Gyimóthy T, Csirik J.  2000.  A Comparative Study of Several Feature Space Transformation and Learning Methods for Phoneme Classification. International Journal of Speech Technology. 2:263-276.

Tóth L, Kocsor A, Kovács K.  2000.  A Discriminative Segmental Speech Model and its Application to Hungarian Number Recognition. Text, Speech and Dialogue: Third International Workshop, TSD 2000, LNAI vol. 1902. :307-313.

Kicsi A, Tóth L, Vidács L.  2018.  Exploring the Benefits of Utilizing Conceptual Information in Test-to-Code Traceability. Proceedings of the IEEE/ACM 6th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE 2018 @ ICSE).

Kicsi A, Tóth L, Vidács L.  2018.  Exploring the Benefits of Utilizing Conceptual Information in Test-to-Code Traceability. Proceedings of the IEEE/ACM 6th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE 2018 @ ICSE).

Paczolay D, Tóth L, Kocsor A, Kerekes J.  2002.  Gépi tanulás alkalmazása egy fonológiai tudatosság-fejlesztõ rendszerben. Alkalmazott Nyelvtudomany. II:55-67.

Kovács K, Kocsor A, Tóth L.  2002.  Hungarian Speech Synthesis Using a Phase Exact HNM Approach. SOFSEM 2002: Theory and Practice of Informatics: 29th Conference on Current Trends in Theory and Practice of Informatics, LNAI vol. 2540. :181-185.

Gosztolya G, Vincze V, Tóth L, Pákáski M, Kálmán J, Hoffmann I.  2019.  Identifying Mild Cognitive Impairment and mild Alzheimer’s disease based on spontaneous speech using ASR and linguistic features. Computer, Speech & Language. 53:181–197.

Tóth L, Nagy B, Vidács L, Gyimóthy T.  2020.  Mining Hypernyms Semantic Relations from Stack Overflow. Proceedings of the First International Workshop on Knowledge Graph for Software Engineering, KG4SE 2020 - ICSEW.

Vicsi K, Tóth L, Kocsor A, Gordos G, Csirik J.  2002.  MTBA - magyar nyelvû telefonbeszéd-adatbázis. Híradástechnika. LVII:35-39.

Kocsor A, Tóth L, Paczolay D.  2001.  A Nonlinearized Discriminant Analysis and its Application to Speech Impediment Therapy. Text, Speech and Dialogue : 4th International Conference, TSD 2001, LNAI vol. 2166. :249-257.

Tóth L, Kocsor A, Kovács K, Felföldi L.  2003.  Nyelvészeti tudásforrások integrálási lehetõségei diszkriminatív szegmens-alapú beszédfelismerõ rendszerekbe. I. Magyar Számítógépes Nyelvészet Konferencia. :169-175.

Kocsor A, Tóth L, Bálint I.  1998.  On the Optimal Parameters of a Sinusoidal Representation of Signals. Conference of PhD students on Computer Sciences, Volume of Extended Abstracts. :61-63.

Kocsor A, Tóth L, Imre B.  1999.  On the Optimal Parameters of a Sinusoidal Representation of Signals. Acta Cybernetica. 14:315-330.

Paczolay D, Kocsor A, Tóth L.  2003.  Real-Time Vocal Tract Length Normalization in a Phonological Awareness Teaching System. Text, Speech and Dialogue: 6th International Conference, TSD 2003, vol. 2807. :309-314.

Tóth L, Gosztolya G.  2019.  Reducing the Inter-speaker Variance of CNN Acoustic Models Using Unsupervised Adversarial Multi-task Training. Proceedings of SPECOM. :481–490.

Gosztolya G, Grósz T, Tóth L.  2020.  Social Signal Detection by Probabilistic Sampling DNN Training. IEEE Transactions on Affective Computing. 10:164–177.

Tóth L, Vidács L.  2019.  Study of The Performance of Various Classifiers in Labeling Non-Functional Requirements. Information Technology and Control. 48:1-16.

Tóth L, Vidács L.  2018.  Study of Various Classifiers for Identification and Classification of Non-Functional Requirements. Proceedings of the 18th International Conference on Computational Science and Its Applications (ICCSA 2018). 10964:492-503.

Tóth L, Nagy B, Janthó D, Vidács L, Gyimóthy T.  2019.  Towards an Accurate Prediction of the Question Quality at Stack Overflow Using a Deep-Learning-Based NLP Approach. Proceedings of ICSOFT 2019, 14th International Conference on Software Technologies. :631-639.

Csapó TGábor, Al-Radhi MSalah, Németh G, Gosztolya G, Grósz T, Tóth L, Markó A.  2019.  Ultrasound-based Silent Speech Interface Built on a Continuous Vocoder. Proceedings of Interspeech. :894–898.