Prof. Dr. Sergio Canazza
University of Padua, Padua, Italy
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Academic Career Length
18Years (2009-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
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Journal Article
Pierluigi BontempiSergio CanazzaFCFilippo Carnovalini
Filippo CarnovaliniARAntonio Rodà
Antonio RodàIn music, the interpreter manipulates the performance parameters in order to offer a sonic rendition of the piece that is capable of conveying specific expressive intentions. Since the 1980s, there has been growing interest in expressive music performance (EMP) and its computational modeling. This research field has two fundamental objectives: understanding the phenomenon of human musical interpretation and the automatic generation of expressive performances. Rule-based, statistical, machine, and deep learning approaches have been proposed, most of them devoted to the classical repertoire, in particular to piano pieces. On the contrary, we introduce the role of expressive performance within popular music and the contemporary ecology of pop music production based on the use of digital audio workstations (DAWs) and virtual instruments. After an analysis of the tools related to expressiveness commonly available to modern producers, we propose a detailed survey of research into the computational EMP field, highlighting the potential and limits of what is present in the literature with respect to the context of popular music, which by its nature cannot be completely superimposed to the classical one. In the concluding discussion, we suggest possible lines of future research in the field of computational expressiveness applied to pop music.
16 April 2013 in Journal of Electrical and Computer Engineering
Journal Article
FBFederica Bressan
Federica BressanSergio CanazzaThis paper presents a methodology for the preservation of audio documents, the operational protocol that acts as the methodology, and an original open source software system that supports and automatizes several tasks along the process. The methodology is presented in the light of the ethical debate that has been challenging the international archival community for the last thirty years. The operational protocol reflects the methodological principles adopted by the authors, and its effectiveness is based on the results obtained in recent research projects involving some of the finest audio archives in Europe. Some recommendations are given for the rerecording process, aimed at minimizing the information loss and at quantifying the unintentional alterations introduced by the technical equipment. Finally, the paper introduces an original software system that guides and supports the preservation staff along the process, reducing the processing timing, automatizing tasks, minimizing errors, and using information hiding strategies to ease the cognitive load. Currently the software system is in use in several international archives.
20 February 2014 in The Scientific World Journal
Journal Article
Daniele SalvatiSergio CanazzaIn this paper, a method to solve the localization of concurrent multiple acoustic sources in large open spaces is presented. The problem of the multisource localization in far-field conditions is to correctly associate the direction of arrival (DOA) estimated by a network array system to the same source. The use of systems implementing a Bayesian filter is a traditional approach to address the problem of localization in multisource acoustic scenario. However, in a real noisy open space the acoustic sources are often discontinuous with numerous short-duration events and thus the filtering methods may have difficulty to track the multiple sources. Incident signal power comparison (ISPC) is proposed to compute DOAs association. ISPC is based on identifying the incident signal power (ISP) of the sources on a microphone array using beamforming methods and comparing the ISP between different arrays using spectral distance (SD) measurement techniques. This method solves the ambiguities, due to the presence of simultaneous sources, by identifying sounds through a minimization of an error criterion on SD measures of DOA combinations. The experimental results were conducted in an outdoor real noisy environment and the ISPC performance is reported using different beamforming techniques and SD functions.
1 March 2016 in Journal of Cultural Heritage
Journal Article
FBFederica Bressan
Federica BressanRBRoberta Bertani
Roberta Bertani
CFClaudio Furlan
Claudio FurlanFSFabio Simionato
Fabio Simionato
Sergio CanazzaJournal Article
With the advent of digital technologies, the computer has become a generalized tool for music production. Music can be seen as a creative form of human–human communication via a computer, and therefore, research on human–computer and computer–human interfaces is very important. This paper, for the Sensors Special Issue on 800 Years of Research at Padova University, presents a review of the research in the field of music technologies at Padova University by the Centro di Sonologia Computazionale (CSC), focusing on scientific, technological and musical aspects of interaction between musician and computer and between computer and audience. We discuss input devices for detecting information from gestures or audio signals and rendering systems for audience and user engagement. Moreover, we discuss a multilevel conceptual framework, which allows multimodal expressive content processing and coordination, which is important in art and music. Several paradigmatic musical works that stated new lines of both musical and scientific research are then presented in detail. The preservation of this heritage presents problems very different from those posed by traditional artworks. CSC is actively engaged in proposing new paradigms for the preservation of digital art.
2 February 2015 in Advances in Human-Computer Interaction
Journal Article
In several application contexts in multimedia field (educational, extreme gaming), the interaction with the user requests that system is able to render music in expressive way. The expressiveness is the added value of a performance and is part of the reason that music is interesting to listen. Understanding and modeling expressive content communication is important for many engineering applications in information technology (e.g., Music Information Retrieval, as well as several applications in the affective computing field). In this paper, we present an original approach to modify the expressive content of a performance in a gradual way, applying a smooth morphing among performances with different expressive content in order to adapt the audio expressive character to the user’s desires. The system won the final stage of Rencon 2011. This performance RENdering CONtest is a research project that organizes contests for computer systems generating expressive musical performances.
About Me
Sergio Canazza is Full Professor at the Department of Information Engineering, University of Padova, where he teaches Foundations of Computer Science (Bachelor’s Degree in Computer Engineering) and Computer Engineering for Music and Multimedia (Master’s Degree in Computer Engineering). He is Director of the Centro di Sonologia Computazionale (CSC),
University of Padova (https://csc.dei.unipd.it/).
His research activity lies at the intersection of computer engineering and
music, integrating information engineering research with musicology, philology and archivistics methodologies. His main research areas include: (a) preservation, restoration, and reactivation of musical and media art cultural heritage; and (b) musical intelligence within the field of
computational co-creativity. He is author or co-author of more than 250 peer-reviewed scientific publications in international journals and conference proceedings
(https://www.dei.unipd.it/~canazza/pubblicazioni_canazza.pdf). He has chaired and served on the scientific committees of numerous international conferences and has acted as European coordinator in several national and international research projects.
He holds a patent in the field of occupational safety. He won two consecutive Golden Palm Awards (2023 and 2024) at the Cannes Artificial Intelligence
Festival, recognizing the world’s most innovative and impactful Artificial Intelligence project.