@Article{cmc.2020.011241,
AUTHOR = {Yongqiang Bao, Qi Shao, Xuxu Zhang, Jiahui Jiang, Yue Xie, Tingting Liu, Weiye Xu},
TITLE = {A Novel System for Recognizing Recording Devices from  Recorded Speech Signals},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {65},
YEAR = {2020},
NUMBER = {3},
PAGES = {2557--2570},
URL = {http://www.techscience.com/cmc/v65n3/40187},
ISSN = {1546-2226},
ABSTRACT = { The field of digital audio forensics aims to detect threats and fraud in audio 
signals. Contemporary audio forensic techniques use digital signal processing to detect 
the authenticity of recorded speech, recognize speakers, and recognize recording devices. 
User-generated audio recordings from mobile phones are very helpful in a number of 
forensic applications. This article proposed a novel method for recognizing recording 
devices based on recorded audio signals. First, a database of the features of various 
recording devices was constructed using 32 recording devices (20 mobile phones of 
different brands and 12 kinds of recording pens) in various environments. Second, the 
audio features of each recording device, such as the Mel-frequency cepstral coefficients 
(MFCC), were extracted from the audio signals and used as model inputs. Finally, 
support vector machines (SVM) with fractional Gaussian kernel were used to recognize 
the recording devices from their audio features. Experiments demonstrated that the 
proposed method had a 93.4% accuracy in recognizing recording devices.},
DOI = {10.32604/cmc.2020.011241}
}