Publication Date

2017

Document Type

Dissertation/Thesis

First Advisor

Liu, Lichuan, 1945-||Fonseca, Benedito

Degree Name

M.S. (Master of Science)

Department

Department of Electrical Engineering

LCSH

Electrical engineering||Sound||Information technology

Abstract

The goal of this thesis is to compare various audio fingerprinting algorithms under a common framework. An audio fingerprint is a compact content-based signature that uniquely summarizes an audio recording. In this thesis, acoustic fingerprints are based on prominent peaks extracted from the spectrogram of the audio signal in question. A spectrogram is a visual representation of the spectrum of frequencies in an audio signal as it varies with time. Some of the applications of audio fingerprinting include but are not limited to music identification, advertisement detection, channel identification in TV and radio broadcasts. Currently, there are several fingerprinting techniques that employ different fingerprinting algorithms. However, there is no study or concrete proof that suggests one algorithm is better in comparison with the other algorithms. In this thesis, some of the feasible techniques employed in audio fingerprint extraction such as Same-Band Frequency analysis, Cross-Band Frequency analysis, use of Mel Frequency Banks, and use of Mel Frequency Cepstral Coefficients (MFCC) are analyzed and compared under the same framework.

Comments

Advisors: Lichuan Liu; Benedito Fonseca.||Committee members: Benedito Fonseca; Lichuan Liu; Donald Zinger.||Includes bibliographical references.||Includes illustrations.

Extent

x, 55 pages

Language

eng

Publisher

Northern Illinois University

Rights Statement

In Copyright

Rights Statement 2

NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.

Media Type

Text

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