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 speak...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.展开更多
An expert system based on the fuzzy set theory has been developed for geological interpretation of Acoustic Seabed Profiling Records(ASPR). After successively extracting each state of several main pattern characterist...An expert system based on the fuzzy set theory has been developed for geological interpretation of Acoustic Seabed Profiling Records(ASPR). After successively extracting each state of several main pattern characteristics shown on the ASPRs, the similarities between this pattern characteristic-state set and the standard ones corresponding to different geological categories of marine sediments are computed respectively By comparillg these values of sidrilarities, the conclusion of geological classification to the ASPR can be derived.展开更多
A computer-based pattern recognition systems has been developed for geological interpretation of Acoustic Sea-bed Profiling Records. Based on practical experience accumu- lated by specialists, the main pattern charact...A computer-based pattern recognition systems has been developed for geological interpretation of Acoustic Sea-bed Profiling Records. Based on practical experience accumu- lated by specialists, the main pattern characteristics of Acoustic Sea-bed Profiling Records (ASPRs) corresponding to typical geological categories of marine sediment layers in the area of the East China Sea have been expressed altogether in 9 aspects, and a dynamic reasoning expert system designed correspondingly. Starting from an initial premise Characteristic and makes the next step reasoning until the final conclusion (i.e. which geological category the sediment layer belongs to.) is derived, in the mean time, for quantitatively estimating the correctness of the final conclusions, the so-called certainty factor is calculated.展开更多
基金supported by the Jiangsu University Student Training Program[SJCX19_0529]the research fund of Nanjing Institute of Engineering[CXY201931]the National Natural Science Foundation of China(61871213).
文摘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.
文摘An expert system based on the fuzzy set theory has been developed for geological interpretation of Acoustic Seabed Profiling Records(ASPR). After successively extracting each state of several main pattern characteristics shown on the ASPRs, the similarities between this pattern characteristic-state set and the standard ones corresponding to different geological categories of marine sediments are computed respectively By comparillg these values of sidrilarities, the conclusion of geological classification to the ASPR can be derived.
基金the National 863 Plan Youth Foundation of China !(820-Q-09).
文摘A computer-based pattern recognition systems has been developed for geological interpretation of Acoustic Sea-bed Profiling Records. Based on practical experience accumu- lated by specialists, the main pattern characteristics of Acoustic Sea-bed Profiling Records (ASPRs) corresponding to typical geological categories of marine sediment layers in the area of the East China Sea have been expressed altogether in 9 aspects, and a dynamic reasoning expert system designed correspondingly. Starting from an initial premise Characteristic and makes the next step reasoning until the final conclusion (i.e. which geological category the sediment layer belongs to.) is derived, in the mean time, for quantitatively estimating the correctness of the final conclusions, the so-called certainty factor is calculated.
