Sub-nyquist audio fingerprinting for music recognition

Kaichun K. Chang; Solon P. Pissis; Jyh-Shing R. Jang; C.S. Iliopoulos

doi:10.1109/CEEC.2010.5767265

Sub-nyquist audio fingerprinting for music recognition

Kaichun K. Chang, Solon P. Pissis, Jyh-Shing R. Jang, C.S. Iliopoulos

Informatics

Research output: Chapter in Book/Report/Conference proceeding › Conference paper

Abstract

In recent years, Compressive Sampling (CS), a new research topic in signal processing, has piqued interest of a wide range of researchers in different fields. In this paper, we present a sub-Nyquist Audio Fingerprinting (AF) system for music recognition, which utilizes CS theory to generate a compact audio fingerpint, and to achieve significant reduction of the dimensionality of the input signal. The presented experimental results demonstrate that by using the CS-based sub-Nyquist AF system, when downsampling to 30%, the average accuracy is 93.43% under various distorted environments, compared to Nyquist sampling methods. The advantages of the proposed process lie in the comparable performance under the sub-Nyquist sampling rate, and more compact audio fingerprint.

Original language	English
Title of host publication	Computer Science and Electronic Engineering Conference (CEEC), 2010 2nd
Publisher	IEEE
Pages	1-5
Number of pages	5
ISBN (Print)	978-1-4244-9029-5
DOIs	https://doi.org/10.1109/CEEC.2010.5767265
Publication status	Published - Sept 2010

Access to Document

10.1109/CEEC.2010.5767265

Cite this

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title = "Sub-nyquist audio fingerprinting for music recognition",

abstract = "In recent years, Compressive Sampling (CS), a new research topic in signal processing, has piqued interest of a wide range of researchers in different fields. In this paper, we present a sub-Nyquist Audio Fingerprinting (AF) system for music recognition, which utilizes CS theory to generate a compact audio fingerpint, and to achieve significant reduction of the dimensionality of the input signal. The presented experimental results demonstrate that by using the CS-based sub-Nyquist AF system, when downsampling to 30%, the average accuracy is 93.43% under various distorted environments, compared to Nyquist sampling methods. The advantages of the proposed process lie in the comparable performance under the sub-Nyquist sampling rate, and more compact audio fingerprint.",

author = "Chang, {Kaichun K.} and Pissis, {Solon P.} and Jang, {Jyh-Shing R.} and C.S. Iliopoulos",

note = "Note: This article was mistakenly omitted from the original IEEE Xplore conference submission. ",

year = "2010",

month = sep,

doi = "10.1109/CEEC.2010.5767265",

language = "English",

isbn = "978-1-4244-9029-5",

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TY - CHAP

T1 - Sub-nyquist audio fingerprinting for music recognition

AU - Chang, Kaichun K.

AU - Pissis, Solon P.

AU - Jang, Jyh-Shing R.

AU - Iliopoulos, C.S.

N1 - Note: This article was mistakenly omitted from the original IEEE Xplore conference submission.

PY - 2010/9

Y1 - 2010/9

N2 - In recent years, Compressive Sampling (CS), a new research topic in signal processing, has piqued interest of a wide range of researchers in different fields. In this paper, we present a sub-Nyquist Audio Fingerprinting (AF) system for music recognition, which utilizes CS theory to generate a compact audio fingerpint, and to achieve significant reduction of the dimensionality of the input signal. The presented experimental results demonstrate that by using the CS-based sub-Nyquist AF system, when downsampling to 30%, the average accuracy is 93.43% under various distorted environments, compared to Nyquist sampling methods. The advantages of the proposed process lie in the comparable performance under the sub-Nyquist sampling rate, and more compact audio fingerprint.

AB - In recent years, Compressive Sampling (CS), a new research topic in signal processing, has piqued interest of a wide range of researchers in different fields. In this paper, we present a sub-Nyquist Audio Fingerprinting (AF) system for music recognition, which utilizes CS theory to generate a compact audio fingerpint, and to achieve significant reduction of the dimensionality of the input signal. The presented experimental results demonstrate that by using the CS-based sub-Nyquist AF system, when downsampling to 30%, the average accuracy is 93.43% under various distorted environments, compared to Nyquist sampling methods. The advantages of the proposed process lie in the comparable performance under the sub-Nyquist sampling rate, and more compact audio fingerprint.

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DO - 10.1109/CEEC.2010.5767265

M3 - Conference paper

SN - 978-1-4244-9029-5

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EP - 5

BT - Computer Science and Electronic Engineering Conference (CEEC), 2010 2nd

PB - IEEE

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