Abstract This paper presents the work carried out by the Centro di Sonologia Computazionale (CSC) of the University of Padua, regarding the reactivation and preservation of time-based media artworks, including computer music, live electronics, performances, and multimedia art installations. During the last few years, the CSC has been developing a specific approach for archiving, documenting, and reactivating time-based media artworks, which led to the definition of the Multilevel Dynamic Preservation (MDP) model. Through in-depth analysis, various approaches are examined in the reactivation of several case studies, including digitisation, restoration, migration, and virtualisation of the artworks. The selected case studies involve various forms of art expression, such as video art, computer music, expanded cinema, and interactive performance. This contribution offers a comprehensive overview of the challenges encountered in the process of reactivating and preserving multimedia art, investigating the possible solutions offered by new technologies in preserving, digitising and virtualizing some of its forms, such as multimedia installations, expanded cinema, and video art performances.

The aim of this article is to present and discuss an innovative methodology aimed at accessing digitized copies of historical tape music audio documents; the methodology leverages on the multimedia and multisensory capabilities of mobile devices to provide an unprecedented level of fruition. In addition to the methodology, and stemming from it, we present an actual software application for Android tablet devices. This novel piece of software was designed and developed in a multidisciplinary team involving engineers as well as musicians, composers, and archivists. The strongest element in our work is the fact that it follows a rigorous process and it is based on the principles of philological awareness ; thus, it also takes into consideration the critical points in the musicologist's domain such as (i) the definition of preservation (i.e., master) copy, (ii) the importance of secondary information, (iii) the history of production and transmission of audio documents.

The important role of the valence and arousal dimensions in representing and recognizing affective qualities in music is well established. There is less evidence for the contribution of secondary dimensions such as potency, tension and energy. In particular, previous studies failed to find significant relations between computable musical features and affective dimensions other than valence and arousal. Here we present two experiments aiming at assessing how musical features, directly computable from complex audio excerpts, are related to secondary emotion dimensions. To this aim, we imposed some constraints on the musical features, namely modality and tempo, of the stimuli.The results show that although arousal and valence dominate for many musical features, it is possible to identify features, in particular Roughness, Loudness, and SpectralFlux, that are significantly related to the potency dimension. As far as we know, this is the first study that gained more insight into the affective potency in the music domain by using real music recordings and a computational approach.

Computational systems for generating expressive musical performances have been studied for several decades now. These models are generally evaluated by comparing their predictions with actual performances, both from a performance parameter and a subjective point of view, often focusing on very specific aspects of the model. However, little is known about how listeners evaluate the generated performances and what factors influence their judgement and appreciation. In this article, we present two studies, conducted during two dedicated workshops, to start understanding how the audience judges entire performances employing different approaches to generating musical expression. In the preliminary study, 40 participants completed a questionnaire in response to five different computer-generated and computer-assisted performances, rating preference and describing the expressiveness of the performances. In the second, “GATM” ( Gruppo di Analisi e Teoria Musicale ) study, 23 participants also completed the Music Cognitive Style questionnaire. Results indicated that music systemizers tend to describe musical expression in terms of the formal aspects of the music, and music empathizers tend to report expressiveness in terms of emotions and characters. However, high systemizers did not differ from high empathizers in their mean preference score across the five pieces. We also concluded that listeners tend not to focus on the basic technical aspects of playing when judging computer-assisted and computer-generated performances. Implications for the significance of individual differences in judging musical expression are discussed.

Adaptive time delay estimation based on blind system identification (BSI) focuses on the impulse responses between a source and a microphone to estimate the time difference of arrival (TDOA) in reverberant environments. In this letter, we consider the adaptive eigenvalue decomposition (AED) BSI method based on the normalized multichannel frequency-domain least mean square (NMCFLMS) algorithm. We show that the use of filter length constraints (FLC) based on the maximum TDOA between microphones improves the performance of the NMCFLMS filter for the localization of different sound types in highly reverberant environments. The experimental results demonstrate the improvement of the proposed method for reverberation times$({\rm RT}_{60})$of up to 2 s. Applications for this method include teleconferencing systems, musical interfaces, videogames, and monitoring systems.

We present a novel approach to locate multiple acoustic sources in far-field environments, in order to solve an interesting problem in different application domain, such as: audio surveillance systems and soundscape analysis frameworks. This approach aims at finding a solution to the ambiguities in Direction Of Arrivals (DOAs) combination caused by simultaneous multiple sources. The algorithm is based on two steps: the separation of the sources by means of beamforming techniques and the comparison of the Incident Signal Power (ISP) spectrum by means of a spectral distance measure. We implemented a prototype, composed by two linear arrays, that has been successfully tested in a real noisy environment.

We present some results on audio restoration obtained with an algorithm that solves the problems of broadband noise filtering, signal parameters tracking, and impulsive noise removal by using the Extended Kalman Filter (EKF) theory. We show that, to achieve maximum performance, it is essential to optimize the EKF implementation. To this purpose, having to cope with the nonstationarity of the audio signal, we use two properly combined EKF filters (forward and backward), and introduce a bootstrapping procedure for model tracking. The careful combination of the proposed techniques and an accurate choice of some critical parameters, allows to improve the performance of the EKF algorithm. The presented procedure is validated by listening tests.

Expression is an important aspect of music performance. It is the added value of a performance and is part of the reason that music is interesting to listen to and sounds alive. Understanding and modeling expressive content communication is important for many engineering applications in information technology. For example, in multimedia products, textual information is enriched by means of graphical and audio objects. In this paper, we present an original approach to modify the expressive content of a performance in a gradual way, both at the symbolic and signal levels. To this purpose, we discuss a model that applies a smooth morphing among performances with different expressive content, adapting the audio expressive character to the user's desires. Morphing can be realized with a wide range of graduality (from abrupt to very smooth), allowing adaptation of the system to different situations. The sound rendering is obtained by interfacing the expressiveness model with a dedicated postprocessing environment, which allows for the transformation of the event cues. The processing is based on the organized control of basic audio effects. Among the basic effects used, an original method for the spectral processing of audio is introduced.