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

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Publisher: SMPTE — White Plains, NY
Doc Type: Conference Paper
Content Type: Original Research
Volume: 2014, No. 10, pp. 1–7
Abstract: 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.
Publication Date: 2014-10-01
DOI: 10.5594/M001571
Link: https://doi.org/10.5594/M001571
Author(s): MICHAEL BABBITTDolby Laboratories San Francisco, CA mgb@dolby.com
Keyword(s): Logging, Reporting, Cloud, Identification
Copyright: © 2014 Society of Motion Picture and Television Engineers, Inc.

Bibliographic Reference(s)

Status Report of the Advanced Television Systems Committee [Active]
1 . Federal Communications Commission , “FCC 11-182A1, Implementation of the Commercial Advertisement Loudness Mitigation (CALM) Act,” December, 2011 . EXTERNAL
3 . Society of Cable Telecommunications Engineers , “Recommendations for Spot Check Loudness Measurements,” SCTE Document DVS-1111, November, 2012 . EXTERNAL
4 . Babbitt Chandler Grant Murrie and Radhakrishnan , “Acquisition, Recovery and Matching of Unique Information from File-based Media for Automated File Detection,” US Patent Application, May, 2013 . EXTERNAL
5 . ATSC A/85:2013, “ATSC Recommended Practice: Techniques for Establishing and Maintaining Audio Loudness for Digital Television,” March, 2013 . EXTERNAL

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MICHAEL BABBITT; Utilizing Unique Information from File-based Media for Automated File Detection, SMPTE Meetings and Conferences ( October 2014); SMPTE, 2014. Available at https://doi.org/10.5594/M001571

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MICHAEL BABBITT; Utilizing Unique Information from File-based Media for Automated File Detection, SMPTE Meetings and Conferences ( October 2014); SMPTE, 2014. Available at https://doi.org/10.5594/M001571

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<span class="citation">MICHAEL BABBITT; <cite>Utilizing Unique Information from File-based Media for Automated File Detection</cite>, SMPTE Meetings and Conferences ( October 2014); SMPTE, 2014. Available at <a href="https://doi.org/10.5594/M001571" target="_blank" rel="noopener">https://doi.org/10.5594/M001571</a></span>

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MICHAEL BABBITT; Utilizing Unique Information from File-based Media for Automated File Detection, SMPTE Meetings and Conferences ( October 2014); SMPTE, 2014
doi: 10.5594/M001571
url: https://doi.org/10.5594/M001571

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MICHAEL BABBITT; <cite id="bib-10-5594-m001571">Utilizing Unique Information from File-based Media for Automated File Detection</cite>, SMPTE Meetings and Conferences ( October 2014); SMPTE, 2014
<span class="doi">10.5594/M001571</span>
</li>