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The Moving Picture, Audio and Data Coding by Artificial Intelligence (MPAI) Context-based Audio Enhancement (CAE) Audio Recording Preservation (ARP) standard provides the technical specifications for a comprehensive framework for digitizing and preserving analog audio, specifically focusing on documents recorded on open-reel tapes. This paper presents a novel envelope derivative-based method designed to be integrated into the ARP standard, for detecting reverse audio sections during the preservation process. The primary objective of this method is to automatically identify segments of audio recorded in reverse. Leveraging derivative-based signal processing algorithms, the system enhances its capability to detect and reverse such sections, thereby reducing errors during the preservation process. This feature not only aids in identifying and correcting errors but also enhances the efficiency of large-scale audio document archiving projects. The systems performance was evaluated using a diverse dataset that includes various musical genres and digitized tapes, demonstrating its strong potential and effectiveness across different types of audio content.
Author (s): Bosi, Marina; Zanini, Fabio; Spanio, Matteo; Russo, Alessandro; Canazza, Sergio
Affiliation:
Center for Computer Research in Music and Acoustics (CCRMA), Stanford University; Centro di Sonologia Computazionale, Dept. Information Engineering, University of Padua; Centro di Sonologia Computazionale, Dept. Information Engineering, University of Padua; Centro di Sonologia Computazionale, Dept. Information Engineering, University of Padua; Centro di Sonologia Computazionale, Dept. Information Engineering, University of Padua
(See document for exact affiliation information.)
AES Convention: 157
Paper Number:10190
Publication Date:
2024-09-27
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Bosi, Marina; Zanini, Fabio; Spanio, Matteo; Russo, Alessandro; Canazza, Sergio; 2024; A novel derivative-based approach for the automatic detection of time-reversed audio in the MPAI/IEEE-CAE ARP international standard [PDF]; Center for Computer Research in Music and Acoustics (CCRMA), Stanford University; Centro di Sonologia Computazionale, Dept. Information Engineering, University of Padua; Centro di Sonologia Computazionale, Dept. Information Engineering, University of Padua; Centro di Sonologia Computazionale, Dept. Information Engineering, University of Padua; Centro di Sonologia Computazionale, Dept. Information Engineering, University of Padua; Paper 10190; Available from: https://aes2.org/publications/elibrary-page/?id=22693
Bosi, Marina; Zanini, Fabio; Spanio, Matteo; Russo, Alessandro; Canazza, Sergio; A novel derivative-based approach for the automatic detection of time-reversed audio in the MPAI/IEEE-CAE ARP international standard [PDF]; Center for Computer Research in Music and Acoustics (CCRMA), Stanford University; Centro di Sonologia Computazionale, Dept. Information Engineering, University of Padua; Centro di Sonologia Computazionale, Dept. Information Engineering, University of Padua; Centro di Sonologia Computazionale, Dept. Information Engineering, University of Padua; Centro di Sonologia Computazionale, Dept. Information Engineering, University of Padua; Paper 10190; 2024 Available: https://aes2.org/publications/elibrary-page/?id=22693
@article{bosi2024a,
author={bosi marina and zanini fabio and spanio matteo and russo alessandro and canazza sergio},
journal={journal of the audio engineering society},
title={a novel derivative-based approach for the automatic detection of time-reversed audio in the mpai/ieee-cae arp international standard},
year={2024},
number={10190},
month={april},}
TY – paper
TI – A novel derivative-based approach for the automatic detection of time-reversed audio in the MPAI/IEEE-CAE ARP international standard
AU – Bosi, Marina
AU – Zanini, Fabio
AU – Spanio, Matteo
AU – Russo, Alessandro
AU – Canazza, Sergio
PY – 2024
JO – Journal of the Audio Engineering Society
VL – 10190
Y1 – April 2024