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Multimedia Archives: New Digital Filters to Correct Equalization Errors on Digitized Audio Tapes
Author(s) -
Niccolò Pretto,
Edoardo Micheloni,
Anthony Chmiel,
Nadir Dalla Pozza,
Dario Marinello,
Emery Schubert,
Sergio Canazza
Publication year - 2021
Publication title -
advances in multimedia
Language(s) - English
Resource type - Journals
eISSN - 1687-5699
pISSN - 1687-5680
DOI - 10.1155/2021/5410218
Subject(s) - computer science , equalization (audio) , speech recognition , digitization , active listening , digital filter , filter (signal processing) , digital audio , matlab , audio signal , multimedia , computer vision , telecommunications , speech coding , decoding methods , communication , sociology , operating system
Multimedia archives face the problem of obsolescing and degrading analogue media (e.g., speech and music recordings and video art). In response, researchers in the field have recently begun studying ad hoc tools for the preservation and access of historical analogue documents. +is paper investigates the active preservation process of audio tape recordings, specifically focusing on possible means for compensating equalization errors introduced in the digitization process. If the accuracy of corrective equalization filters is validated, an archivist or musicologist would be able to experience the audio as a historically authentic document such that their listening experience would not require the recovery of the original analogue audio document or the redigitization of the audio. +us, we conducted a MUSHRA-inspired perception test (n 14) containing 6 excerpts of electronic music (3 stimuli recorded NAB and 3 recorded CCIR). Participants listened to 6 different equalization filters for each stimulus and rated them in terms of similarity. Filters included a correctly digitized “Reference,” an intentionally incorrect “Foil” filter, and a subsequent digital correction of the Foil filter that was produced with aMATLAB script.When stimuli were collapsed according to their filter type (NAB or CCIR), no significant differences were observed between the Reference and MATLAB correction filters. As such, the digital correction appears to be a promising method for compensation of equalization errors although future study is recommended, specifically containing an increased sample size and additional correction filters for comparison.

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