Utilizing Unique Information from File-based Media for Automated File Detection

In the United States, the inception of the Commercial Advertisement Loudness Mitigation Act, aka the CALM Act, has created some confusion and uncertainty within broadcast organizations regarding both infrastructure (tools, workflow, logging, etc.) and compliance. While the Federal Communications Commission (FCC) has defined compliance in relatively concrete terms in FCC Report and Order (R&O) 11-182, “Implementation of the Commercial Advertisement Loudness Mitigation (CALM) Act¹”, how esactly to achieve compliance relative to the FCC's implementation directives remains unclear. For many broadcasters and operators, CALM compliance remains somewhat of a mystery and most frequently involves a significant amount of manual effort and expense. — This paper proposes a new method of achieving CALM compliance through a novel approach to program detection using existing file-based media processing tools and widely accepted “cloud-based” network systems and a new, out-of-band, data analysis system to create a fully automated method of program measurement, logging and CALM compliance reporting. Accurate identification of programming subject to the CALM Act additionally allows high value programming like movies and scripted shows to be conveyed with cinematic audio attributes like high dynamic range and not be inadvertently or purposefully processed unnecessarily to achieve compliance according to CALM statute requirements.

Published

2014-10

Content type

Original Research

Keywords

CALM Act, Loudness Control, Automated Program Detection, Fingerprint, Logging, Reporting, Compliance, Program Boundary, Cloud, Identification

DOI

10.5594/M001571

ISBN

978-1-61482-954-6