A new derivative-based model for the automatic detection of time-reversed audio in the MPAI/IEEE-CAE ARP international standard

This work introduces a novel, envelope derivative-based method to detect reverse audio sections present in an audio document. The proposed method was born to be incorporated in the MPAI/IEEE-CAE ARP standard. 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. The primary objective of this project was that of developing a method to automatically identify segments of audio recorded in reverse, in order to use the algorithm during the digitization process of open-reel magnetic tapes. Leveraging advanced derivative-based signal processing algorithms, the system enhances its capability to detect such reversed sections, thereby reducing errors during the analog-to-digital (A/D) conversion. This feature not only aids in identifying and correcting digitization errors but also improves the efficiency of large-scale audio document digitization projects. The system's performance has been evaluated using a diverse dataset encompassing various musical genres and digitized tapes, demonstrating its effectiveness across different types of audio content.