The Transmission of Digital Audio: Data Formats

Author(s):  
Wallace Jackson
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.


1995 ◽  
Vol 7 (1) ◽  
pp. 5-10 ◽  
Author(s):  
F. Wylie

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 ◽  
...  

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.


2015 ◽  
Vol 743 ◽  
pp. 355-358
Author(s):  
Mang Zhou

This paper describes a audio system for high-definition(HD)digital audio decoding solution. The system is well aligned to decoding audio data stream Dolby True HD,DTS HDMaster, and support advanced audio processing Pro Logic® IIx, DTS Neo6. Discuss focuses on system construction and management of audio process by host MUC.


Sign in / Sign up

Export Citation Format

Share Document