Digital audio data compression

1995 ◽  
Vol 7 (1) ◽  
pp. 5-10 ◽  
Author(s):  
F. Wylie
2000 ◽  
Vol 108 (1) ◽  
pp. 449-452 ◽  
Author(s):  
B. E. Rulon ◽  
M. F. Shaw ◽  
K. D. Donohue

2003 ◽  
pp. 139-144
Author(s):  
Richard Brice
Keyword(s):  

2019 ◽  
Vol 11 (2) ◽  
pp. 47-62 ◽  
Author(s):  
Xinchao Huang ◽  
Zihan Liu ◽  
Wei Lu ◽  
Hongmei Liu ◽  
Shijun Xiang

Detecting digital audio forgeries is a significant research focus in the field of audio forensics. In this article, the authors focus on a special form of digital audio forgery—copy-move—and propose a fast and effective method to detect doctored audios. First, the article segments the input audio data into syllables by voice activity detection and syllable detection. Second, the authors select the points in the frequency domain as feature by applying discrete Fourier transform (DFT) to each audio segment. Furthermore, this article sorts every segment according to the features and gets a sorted list of audio segments. In the end, the article merely compares one segment with some adjacent segments in the sorted list so that the time complexity is decreased. After comparisons with other state of the art methods, the results show that the proposed method can identify the authentication of the input audio and locate the forged position fast and effectively.


Computing ◽  
2019 ◽  
Vol 102 (3) ◽  
pp. 813-827 ◽  
Author(s):  
Weiping Tu ◽  
Yuhong Yang ◽  
Bo Du ◽  
Wanzhao Yang ◽  
Xiong Zhang ◽  
...  

2009 ◽  
Author(s):  
Sascha Zmudzinski ◽  
Martin Steinebach
Keyword(s):  

2002 ◽  
Vol 112 (5) ◽  
pp. 1739
Author(s):  
Donald S. Lydon ◽  
Charles S. Meyer
Keyword(s):  

Author(s):  
Arief Bramanto Wicaksono Putra ◽  
Muhammad Taher Jufri ◽  
Dirgahayu Lantara ◽  
Anugrah Assyauqi ◽  
Agusma Wajiansyah ◽  
...  

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