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A Robust Audio DNA-Based Method for OTT Content Recognition in Noisy Environment

  • Journal of Software Assessment and Valuation
  • Abbr : JSAV
  • 2025, 21(2), pp.21~31
  • Publisher : Korea Software Assessment and Valuation Society
  • Research Area : Engineering > Computer Science
  • Received : April 24, 2025
  • Accepted : June 20, 2025
  • Published : June 30, 2025

Byuong-Chan Park 1 Seyoung Jang 1 Seok-Yoon Kim 1 Youngmo Kim 1

1숭실대학교

Accredited

ABSTRACT

With the increasing use of OTT content, there is a growing demand for copyright protection across diverse playback environments. In particular, technologies capable of identifying original audio even under the presence of unstructured noise—such as white noise or conversational background noise—are gaining importance. This paper proposes a robust method for extracting and recognizing audio DNA that remains reliable in such noisy conditions. By leveraging feature extraction based on MEL spectrograms, the proposed system generates a dual-stage fingerprint structure consisting of coarse and fine features. Recognition performance was evaluated under various parameter combinations. Experimental results demonstrate that by optimizing FFT length and feature dimension, the proposed method achieves high accuracy. The results confirm that the approach can be effectively applied to real-time content authentication and copyright protection systems in OTT service environments.

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