## 1 Introduction
The generation process of sets of ND images or video sequences can be well described by means of a structure called an image or video phylogeny tree (IPT or VPT), and several algorithms have been recently proposed in the literature to reconstruct it [14; 15; 16]. Most of the proposed solutions analyze the relations between similar contents and infer the subset of links that correctly represents the chains of dependencies and transformations. Although, in the last few years, several works have been targeting the analysis of images and video contents, little effort has been put toward audio phylogenetic approaches. To the best of our knowledge, the only algorithms proposed in the literature are represented by [17; 12]. Moreover, the phylogenetic analysis problems have been extensively investigated for digital multimedia contents since online material offers the largest datasets of near-duplicate contents. The investigation of phylogenetic approaches involving audio-visual contents stored on magnetic carriers is still at its earliest stages. In the end, multimedia phylogenetic strategies have been employed for copyright infringement detection and fake material identification; their use in cultural heritage and multimedia restoration is one of the novelty aspects presented by this paper. The authors propose in the following sections an automated approach to stemmatics, applying a phylogenetic evolutionary framework to music digital philology. Different witnesses (audio files) are analyzed by software developed by the authors and then grouped according to their shared characteristics, listed in a tree in order to derive relationships between them (Figure 1). The current paper presents a novel methodology that automatizes the creation of such a dependency tree and proves to be sufficiently robust to acquisition errors (wrong reading speed or setup). The proposed solution relies on collecting the tapes to be analyzed into a set of digital audio tracks and representing them by means of two-dimensional spectrograms. After aligning them using computer vision strategies, it is possible to infer the most likely transformation interplay between them and to characterize it via a dissimilarity metric. Such dissimilarity metrics are then used to characterize the edge weights of a complete graph where nodes correspond to the acquired audio tracks. By running a minimum spanning tree (MST) algorithm, it is possible to estimate the phylogenetic tree that links the different contents. Experimental data show that the proposed solution permits reconstructing the underlying story of each tape with good accuracy; moreover, the reconstruction process is not affected by digitization errors such as a different reading speed, wrong equalization and filtering. The results achieved show that this methodology gives a precise answer to the questions about the reliability of audio recordings as document witnesses, clarifying the concept of fidelity to the original. In the following, the paper is organized as follows. Section 2 overviews some of the related works in the literature, while Section 3 describes how the phylogenetic reconstruction problem can be applied to magnetic tapes. Then, the full methodology is presented in Section 4, together with the reconstruction algorithm that permits estimating the audio phylogenetic tree (APT). This strategy is then evaluated on an experimental dataset (described in Section 5), and the obtained results are reported and discussed in Section 6. Section 7 draws the final conclusions.