The project team includes the leading FTS and MI researchers at the project of technological development TR32035 "The development of dialog systems for Serbian and other South Slavic languages" carried out from 2011 to 2019, with financial support from the Ministry of Education, Science and Technological Development. An interesting fact is that the first 12 AI projects accepted in Serbia include another project with researchers previously participating in TR32025 – the project led by prof. Zoran Perić, PhD, of the Faculty of Electronics in Niš. The project S-ADAPT addresses paralinguistic aspects of human-machine speech communication, which encompass various speech styles and emotional expressions, which is why the project logo shows the faces of project team members in different emotional states.
Vlado Delić is the PI of the Project and the leader of the Speech Technology group at the Department of Power, Electronic and Telecommunication Engineering at FTS-UNS, which has been dedicated to the development of speech technologies for over 20 years. He is the principal lecturer at the course “Human-machine speech communication” at the PhD studies at FTS-UNS, and under his mentorship more than 10 PhD theses in this area have been prepared and defended, including the theses of Project team members Milan Sečujski, Branislav Popović and Siniša Suzić.
Aleksandra Pižurica is a team member as a consultant from diaspora. She is the Head of the Group for Artificial Intelligence and Sparse Modelling (GAIM) at the Department of Telecommunications and Information Processing (TELIN), University of Ghent, Belgium.
Milan Sečujski is a leading researcher in computational linguistics and natural language processing with over 160 scientific publications, who has given a key contribution to the development of speech and language resources for Serbian and kindred languages, as well as intonation modelling. He authored the only existing morphological dictionaries of Serbian and Croatian explicitly listing inflected word forms (more than 5 million each), which form the basis for all speech technology applications in these two standard variants of Serbo-Croatian, and developed a prosodic annotation system for them (used for structuring speech data and marking it for prosodic events such as accents, phrase breaks and sentence emphasis). He is also the principal lecturer at the courses “Machine learning 1” and “Machine learning 2” at two BSc study programmes at FTS-UNS, and participates as lecturer at the course “Speech technology” at the MSc studies of Power Engineering, Electronics and Telecommunications at FTS-UNS.
Branislav Popović is a leading researcher and the youngest PhD at FTS-UNS with more than 60 publications in the area of speech technology, including both acoustic and language modelling (PhD thesis: “Hierarchical clustering of Gaussian mixture models in applications for continuous speech recognition”, under the mentorship of Vlado Delić, 2012). He was also the principal lecturer at the course “Artificial Intelligence” at the Faculty of Information Technology as well as the Faculty of Mathematics and Computer Science of the Alfa BK University in Belgrade, and participates as lecturer at the course “Speech technology” at the MSc studies of Power Engineering, Electronics and Telecommunications at FTS-UNS.
Marko Janev is a senior research associate from the Mathematical Institute of the Serbian Academy of Sciences and Arts (MI-SANU), with great experience in both image processing and general machine learning (PhD thesis: “Application of Fractional Calculus in Image Denoising”, 2011)
Lidija Krstanović is a researcher with expertise in applied mathematics, machine learning and image processing (PhD thesis: “GMMs Similarity Measure Based on Transformation of the Parameter Space”, 2017). Lidija Krstanović is also the principal lecturer at the course “Artificial Intelligence” at the MSc study programme Animation in Engineering at FTS-UNS.
Nikola Simić is a researcher with a wide experience of autoencoding and compression techniques, which will be of a great importance for efficient inference using neural networks (PhD thesis: “The designing of quantizers in signal compression algorithms”, 2019).
Siniša Suzić defended his PhD thesis in 2019, entitled “Parametric synthesis of expressive speech”, under the mentorship of Vlado Delić. The latest research of the team for speech synthesis (TTS), professor Milan Sečujski, together with associates Siniša Suzić and Tijana Nosek, has resulted in 3 papers in international journals and a number of international conference papers dealing with speaker/style adaptation in TTS based on neural networks.
Nina Maljković is the youngest team member. She is a junior research assistant and the best student of her generation at the MSc studies of Signal Processing at FTS-UNS.