Content-Based Audio Retrieval

2021 ◽  
pp. 361-420
Author(s):  
Meinard Müller
Keyword(s):  
Audio Retrieval

Method of specific audio retrieval based on randomly segment

2010 ◽  
Vol 30 (1) ◽  
pp. 230-232
Author(s):  
Ji-chen YANG ◽  
Wei-ning WANG
Keyword(s):  
Audio Retrieval

An Inverted Index Based Audio Retrieval Method

2013 ◽  
Vol 34 (11) ◽  
pp. 2561-2567 ◽  
Author(s):  
Xue-yuan Zhang ◽  
Qian-hua He ◽  
Yan-xiong Li ◽  
Wan-ling Ye
Keyword(s):  
Inverted Index ◽  
Retrieval Method ◽  
Audio Retrieval

Features for Content-Based Audio Retrieval

2010 ◽  
pp. 71-150 ◽  
Author(s):  
Dalibor Mitrović ◽  
Matthias Zeppelzauer ◽  
Christian Breiteneder
Keyword(s):  
Audio Retrieval

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

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.

Content-Based Audio Retrieval

2015 ◽  
pp. 355-413 ◽  
Author(s):  
Meinard Müller
Keyword(s):  
Audio Retrieval
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