A Robust Audio Fingerprinting Using a New Hashing Method

Heui-Su Son,Seok-Pil Lee,Sung-Woo Byun

doi:10.1109/access.2020.3024951

Heui-Su Son, Seok-Pil Lee + Show 1 more

Open Access

https://doi.org/10.1109/access.2020.3024951

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Abstract

To enhance the tracking performance of illegal audio copies, we introduce a robust audio fingerprinting method against various attacks in this paper. Most audio fingerprints consist of the information in the frequency band of audio. These fingerprinting methods may lose the uniqueness of the audio fingerprint by irregular movement such as an attack with pitch value changes. The proposed fingerprint method in a fundamental frequency band makes up for the weakness of existing methods generated from frequency domain. Using the geometrical property of the proposed method, a new hashing method is employed in the similarity calculation process to compare the audio contents. In order to prove the validity of proposed algorithm, we experiment for six environments such as tempo, pitch, speed modification, noise addition, low pass filter and high pass filter. The proposed method shows the highest level of performance in most experimental environments. Especially, with respect to the tempo, pitch, and speed manipulation experiments, the proposed method archives the precision rate of the range from 95 to 100% according to the degree of manipulation, which compares favorably with the precision rate obtained by traditional approaches, and yields a precision rate between 85 and 100% in noise addition and filtering experiments.

Highlights

Media platforms such as YouTube have been growing at a fast rate, in the distribution and sharing of media contents
EXPERIMENTS we present the performances of proposed fundamental frequency map (FFMAP) based audio fingerprinting method
The fundamental frequency components extracted from an audio data are matched with frame-fundamental frequency domain and compose fundamental frequency map (FFMAP)

Summary

Introduction

Media platforms such as YouTube have been growing at a fast rate, in the distribution and sharing of media contents. A lot of content can be searched, especially audio contents [1]. This makes being able to access and enjoy the desired contents through various platforms, but causes many problems like illegal copies simultaneously [2]. Copyright infringement of audio data is a representative example. As the illegal use and the prohibited distribution of contents are constantly increasing, studies are ongoing to protect the copyright of the original audio and to detect illegally used data [3]–[5]. Anyone is able to copy and distribute audio content accessed on the internet. The necessity of copyright protection technology for audio data comes to the fore.

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