STUDY ON FRAMEWORK OF AUDIO FINGERPRINTING AND SHAZAM?S WORKING ALGORITHM.

Active fingerprinting combines digital media watermarking and codes for collusion-secure customer identification. This requires specialized strategies for watermark embedding to lessen the thread of attacks like marked media comparison or mixing. We introduce basic technologies for fingerprinting and digital watermarking and possible attacks against active fingerprinting. Based on this, we provide test results, discuss the consequences and suggest an optimized embedding method for audio fingerprinting.

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A Hierarchical Retrieval Method Based on Hash Table for Audio Fingerprinting

Intelligent Computing Theories and Application - Lecture Notes in Computer Science ◽

10.1007/978-3-030-84522-3_13 ◽

2021 ◽

pp. 160-174

Author(s):

Tianhao Li ◽

Maoshen Jia ◽

Xuan Cao

Keyword(s):

Hash Table ◽

Retrieval Method ◽

Audio Fingerprinting

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Audio Signal Identification and Search Approach for Minimizing the Search Time in Audio Fingerprinting Using Template Matching

Advanced Computational Intelligence An International Journal (ACII) ◽

10.5121/acii.2016.3203 ◽

2016 ◽

Vol 3 (2) ◽

pp. 23-33

Author(s):

Mohammed Ahmed ◽

Swaleha Shaikh ◽

Hera Ansari ◽

Arshi Siddiqui

Keyword(s):

Template Matching ◽

Search Time ◽

Audio Signal ◽

Signal Identification ◽

Audio Fingerprinting ◽

Search Approach

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Daubechies Wavelets Based Robust Audio Fingerprinting for Content-Based Audio Retrieval

International Journal of Digital Crime and Forensics ◽

10.4018/jdcf.2012040104 ◽

2012 ◽

Vol 4 (2) ◽

pp. 49-69

Author(s):

Wei Sun ◽

Zhe-Ming Lu ◽

Fa-Xin Yu ◽

Rong-Jun Shen

Keyword(s):

Wavelet Transforms ◽

Wavelet Decomposition ◽

Experimental Results ◽

Daubechies Wavelet ◽

Linear Speed ◽

Time Frequency ◽

Audio Fingerprinting ◽

Audio Retrieval ◽

Audio Clip ◽

Frequency Features

Audio fingerprinting is the process to obtain a compact content-based signature that summarizes the essence of an audio clip. In general, existing audio fingerprinting schemes based on wavelet transforms are not robust against large linear speed changes. The authors present a novel framework for content-based audio retrieval based on the audio fingerprinting scheme that is robust against large linear speed changes. In the proposed scheme, 8 levels Daubechies wavelet decomposition is adopted for extracting time-frequency features and two fingerprint extraction algorithms are designed. The experimental results from this study are discussed further into the article.

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