Matteo Spanio

CSC lab, building DEI/S

Via Gardenigo 6/A

Padua, Italy

Hi there, I’m Matteo Spanio, Ph. D. student at the University of Padua. I’m interested in:

🤖 machine learning,
📡 signal processing,
🎹 music.

My Ph. D. project focuses on studying deep learning methods for music generation based on cross modal perception.

I’m member of the MPAI group, the international, unaffiliated, no-profit organisation developing standards for AI-based data coding.

I’m also a musician, and I play the clarinet on a regular basis in many orchestras and ensembles (Orchestra di Padova e del Veneto, Orchestra del Friuli Venezia Giulia, Orchestra San Marco, Concordia Chamber Orchestra, Rossini Ensemble and many others).

To see my work, check out my projects and publications. Time permitting, I also write blog posts.

news

Sep 11, 2023	Today Dr. Alessandro Russo is presenting our new article “Enhancing Preservation and Restoration of Open Reel Audio Tapes Through Computer Vision” at the International Conference of Image Analysis and Processing (ICIAP 2023) in Udine, see you there.
Jul 23, 2023	New blog layout is now live! It’s based on al-folio

latest posts

Nov 10, 2023	Python's Static Typing Safari: In Search of Code Clarity
Aug 30, 2022	Principles of statistic
Jul 10, 2021	DSP: il suono in digitale

selected publications

ICIAP2023
Enhancing Preservation and Restoration of Open Reel Audio Tapes Through Computer Vision

Alessandro Russo, Matteo Spanio, and Sergio Canazza

In Image Analysis and Processing - ICIAP 2023 Workshops, 2024

Abs Bib

Analog audio documents inevitably face degradation over time, posing a challenge for preserving their audio content and ensuring the integrity of the recordings. Analog document preservation is one of the main research topics of interest of the Centro di Sonologia Computazionale (CSC) of the Department of Information Engineering of the University of Padua, which over the years developed and implemented a methodology for preservation that includes, among other things, the video recording of the digitization process of the open-reel tapes for documenting irregularities on the top of their surface. Together with the corpus of digitized high-quality audio recordings, this led to the creation of an internal archive of video documents. This paper presents a software application that leverages computer vision techniques to automatically detect Irregularities on open-reel audio tapes, analyzing the video documents produced during the digitization interventions. The software employs a frame-by-frame analysis to automatically identify and highlight points of interest that may indicate tape damages, splices, and other Irregularities. The software uses Generalized Hough Transform and SURF algorithms to locate regions of interest within the tape. The proposed software is also part of the MPAI/IEEE-CAE ARP standard developed by Audio Innova s.r.l., spin-off of the CSC, and it may offer a robust and efficient solution for analyzing open-reel audio tapes, supporting archivists and musicologists in their activities.
@inproceedings{10.1007/978-3-031-51026-7_26, language = {en}, doi = {10.1007/978-3-031-51026-7_26}, url = {https://doi.org/10.1007/978-3-031-51026-7_26}, author = {Russo, Alessandro and Spanio, Matteo and Canazza, Sergio}, editor = {Foresti, Gian Luca and Fusiello, Andrea and Hancock, Edwin}, title = {Enhancing Preservation and Restoration of Open Reel Audio Tapes Through Computer Vision}, booktitle = {Image Analysis and Processing - ICIAP 2023 Workshops}, year = {2024}, publisher = {Springer Nature Switzerland}, address = {Cham}, pages = {297--308}, isbn = {978-3-031-51026-7} }