Matevž is an assistant professor (PhD) and a researcher at the Faculty of Computer and Information Science, University of Ljubljana. He received his B.Sc. in computer science in 2012 and his PhD in 2018. He is a member of the Laboratory of Computer Graphics and Multimedia since 2009. His research interests are biologically-inspired models, deep architectures including compositional hierarchical modelling and music multi-modal perception, including human-computer interaction, and visualization for audio analysis and music generation.

Publications

My CV can be found here.

If interested, please follow my work on ResearchGate: Matevž Pesek on ResearchGate

Journals

• M. Pesek, L. Suhadolnik, P. Šavli, and M. Marolt, “Motivating students for ear-training with a rhythmic dictation application,” Applied sciences, vol. 10, iss. 19, pp. 1-19, 2020.
  https://www.mdpi.com/2076-3417/10/19/6781
• M. Pesek, Ž. Vučko, P. Šavli, A. Kavčič, and M. Marolt, “Troubadour : a gamified e-learning platform for ear training,” IEEE access, iss. 8, pp. 97090-97102, 2020. Available: https://ieeexplore.ieee.org/document/9093057
• M. Pesek, A. Leonardis, and M. Marolt, “An analysis of rhythmic patterns with unsupervised learning,” Applied sciences, vol. 10, iss. 1, pp. 1-22, 2020.
  Available: https://www.mdpi.com/2076-3417/10/1/178
•  M. Marolt, C. Bohak, A. Kavčič, and M. Pesek, “Automatic segmentation of ethnomusicological field recordings,” Applied sciences, vol. 9, iss. 3, pp. 1-12, 2019. Available: https://www.researchgate.net/publication/330710734_Automatic_Segmentation_of_Ethnomusicological_Field_Recordings
• M. Pesek, A. Leonardis, and M. Marolt, “SymCHM – an unsupervised approach for pattern discovery in symbolic music with a compositional hierarchical model,” Applied sciences, vol. 7, iss. 11, pp. 1-21, 2017. Available: www.mdpi.com/2076-3417/7/11/1135
•  M. Pesek, A. Leonardis, and M. Marolt, “Robust real-time music transcription with a compositional hierarchical model,” PloS one, vol. 12, iss. 1, pp. 1-21, 2017. Available: journals.plos.org/plosone/article?id=10.1371/journal.pone.0169411
  
• M. Pesek, G. Strle, A. Kavčič, and M. Marolt, “The Moodo dataset : integrating user context with emotional and color perception of music for affective music information retrieval,” Journal of new music research, pp. 1-15, 2017. http://www.tandfonline.com/doi/full/10.1080/09298215.2017.1333518?scroll=top&needAccess=true
•  M. Pesek, G. Strle, and M. Marolt, “Uporabniški vmesniki in metodologija pridobivanja večmodalnih podatkov o glasbi,” Elektrotehniški vestnik, vol. 82, iss. 3, pp. 93-101, 2015.

Books

• G. Strle, M. Pesek, M. Marolt – Towards User-Aware Music Information Retrieval: Emotional and Color Perception of Music; Emotions and Personality in Personalized Services; 2016. http://link.springer.com/chapter/10.1007/978-3-319-31413-6_16
• M. Pesek, G. Strle, J. Guna, E. Stojmenova, M. Pogačnik, M. Marolt – Towards a Personalised and Context-Dependent User Experience in Multimedia and Information Systems; Information Systems and Management in Media and Entertainment Industries; 2016. http://link.springer.com/chapter/10.1007/978-3-319-49407-4_8

Conferences

•  M. Pesek, A. Isaković, G. Strle, and M. Marolt, “Improving the usability of online usability surveys with an interactive Stripe scale,” in Interakcija človek-računalnik v informacijski družbi : zbornik 19. mednarodne multikonference Informacijska družba – IS 2016, 11. oktober 2016, [Ljubljana, Slovenija] : zvezek E : proceedings of the 19th International Multiconference Information Society – IS 2016, 11 October 2016, Ljubljana, Slovenia : volume E, 2016, pp. 21-24.
•  M. Pesek, A. Leonardis, and M. Marolt, “SymCHMMerge – hypothesis refinement for pattern discovery with a compositional hierarchical model,” in MML 2016 : proceedings : held in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, (ECML/PKDD 2016), 2016, pp. 46-50.
•  M. Pesek, A. Leonardis, and M. Marolt, “Pattern discovery and music similarity with compositional hierarchical model,” in CogMIR : August 12, 2016, Columbia University, New York, 2016, p. 8.
•  G. Strle, M. Pesek, and M. Marolt, “Emotions and personality in personalized services : models, evaluation and applications.” [S. l.] : Springer, cop. 2016, 2016, pp. 327-353.
•  M. Pesek, D. Kuhl, M. Baloh, and M. Marolt, “ZaznajSpoznaj – a modifiable platform for accessibility and inclusion of visually-impaired elementary school children,” in Proceedings / International Conference on Informatics in Schools – ISSEP 2015, September 28 – October 1, Ljubljana, Slovenia, 2015, pp. 173-179.
• M. Pesek, A. Leonardis, and M. Marolt, “Towards pattern discovery in symbolic music representations using a compositional hierarchical model,” in Zbornik štiriindvajsete mednarodne Elektrotehniške in računalniške konference ERK 2015, 21. – 23. september 2015, Portorož, Slovenija, 2015, pp. 57-60.
•  M. Pesek, L. Zakrajšek, and M. Marolt, “WEBCHM : an online tool for music analysis, transcription and annotation,” in ISMIR 2015, 2015, pp. 1-2.
• M. Pesek, A. Leonardis, and M. Marolt, “Boosting audio chord estimation using multiple classifiers,” in IWSSIP 2014 : proceedings, 2014, pp. 107-110.
•  C. Bohak, A. Sodja, M. Marolt, U. Mitrović, and F. Pernuš, “Fast segmentation, conversion and rendering of volumetric data using GPU,” in IWSSIP 2014 : proceedings, 2014, pp. 239-242.
• M. Pesek, P. Godec, M. Poredoš, G. Strle, J. Guna, E. S. Duh, M. Pogačnik, and M. Marolt, “Gathering a dataset of multi-modal mood-dependent perceptual responses to music,” in UMAP 2014 extended proceedings : posters, demos, late-breaking results and workshop proceedings of the 22nd Conference on User Modeling, Adaptation, and Personalization, Aalborg, Denmark, July 7-11, 2014, 2014, pp. 1-12.
• M. Pesek, P. Godec, M. Poredoš, G. Strle, J. Guna, E. S. Duh, M. Pogačnik, and M. Marolt, “Capturing the mood : evaluation of the moodstripe and moodgraph interfaces,” in ICME 2014, 2014, pp. 1-5.
•  A. Kavčič, C. Bohak, M. Pesek, and M. Marolt, “Edoo : involving teachers in the development of e-learning material,” in Open education for a multicultural world : OCWC Global Conference, 23-25 April Ljubljana, Slovenia, 2014, pp. 1-4.
•  M. Pesek, A. Leonardis, and M. Marolt, “A compositional hierarchical model for music information retrieval,” in Proceedings of the 15th Conference of the International Society for Music Information Retrieval, ISMIR 2014, October 27-31, 2014, Taipei, Taiwan, 2014, pp. 131-136.
•  M. Pesek, P. Godec, M. Poredoš, G. Strle, J. Guna, E. S. Duh, M. Pogačnik, and M. Marolt, “Introducing a dataset of emotional and color responses to music,” in Proceedings of the 15th Conference of the International Society for Music Information Retrieval, ISMIR 2014, October 27-31, 2014, Taipei, Taiwan, 2014, pp. 355-360.
• M. Pesek, P. Godec, M. Poredoš, G. Strle, J. Guna, E. S. Duh, M. Pogačnik, and M. Marolt, “The MoodStripe – an evaluation of a novel visual interface as an alternative for online response gathering,” in Proceedings of the 7th International Workshop on Semantic Ambient Media Experience (SAME 2014) – Ambient Media Usability, Interaction, and Smart Media Technologies : Helsinki, Finland, 26th October 2014, 2014, pp. 1-4.
• M. Žerovnik, M. Pesek, and M. Marolt, “Ocenjevanje osnovnih frekvenc z uporabo kompozicionalnega hierarhičnega modela,” in Zbornik triindvajsete mednarodne Elektrotehniške in računalniške konference ERK 2014, 22. – 24. september 2014, Portorož, Slovenija, 2014, pp. 265-268.
• P. Godec, M. Pesek, M. Poredoš, G. Strle, J. Guna, E. S. Duh, M. Pogačnik, and M. Marolt, “New dataset of emotional and color responses to music,” in Zbornik triindvajsete mednarodne Elektrotehniške in računalniške konference ERK 2014, 22. – 24. september 2014, Portorož, Slovenija, 2014, pp. 309-312.
• M. Pesek, A. Leonardis, and M. Marolt, “A preliminary evaluation of robustness to noise using the compositional hierarchical model for music information retrieval,” in Zbornik triindvajsete mednarodne Elektrotehniške in računalniške konference ERK 2014, 22. – 24. september 2014, Portorož, Slovenija, 2014, pp. 104-107.
• M. Pesek, A. Leonardis, and M. Marolt, “Compositional hierarchical model for pattern discovery in music,” in EuroMAC 2014 : abstracts : Eight European Music Analysis Conference, 17-20 September 2014, Leuven, 2014, p. 288.
• M. Pesek, “Visualizing the compositional hierarchical model : the goal,” in HAMR : hacking audio and music research, Oct. 25-26, 2014, Taipei, Taiwan, 2014, p. 1.