A mobile phone source identification method in additive noise environment based on fusion features
A technology that integrates features and additive noise. It is applied in speech analysis, instruments, etc. It can solve problems such as poor robustness and difficult recognition, and achieve the effect of ensuring accuracy, improving recognition effect, and strong noise robustness.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Publication Date
- 2021-11-09
Smart Images

Figure 1 
Figure 2 
Figure 3
Abstract
Description
technical field
[0001] The invention relates to the technical field of mobile phone source identification, in particular to a method for identifying mobile phone source in an additive noise environment based on fusion features. Background technique
[0002] With the development of information technology, easy-to-carry mobile phones are becoming more and more popular, and many people are accustomed to using mobile phones to record voices. Therefore, research on source identification based on mobile phone recording devices has received extensive attention. In recent years, some research results have been obtained on the source identification of mobile phone recording equipment based on quiet environment.
[0003] C.Hanilci et al. extracted the Mel-frequency cepstral coefficient (MFCC) from the recording file as the distinguishing feature of the device, and compared the recognition of the device by the two classifiers SVM and VQ. The set recognition rate analysis found that th...
Examples
Embodiment Construction
[0036] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.
[0037] A method for identifying the source of mobile phones in an additive noise environment based on fusion features proposed by the present invention, its overall realization block diagram is as follows figure 1 As shown, it includes the following steps:
[0038] Step 1: Select M mobile phones of different mainstream brands and models; then use each mobile phone to obtain P speech samples corresponding to N individuals, and each mobile phone corresponds to a total of N×P speech samples; All speech samples constitute a subset, and a total of M × N × P speech samples of M subsets constitute a basic speech library; wherein, M≥10, M=24 in this embodiment, N≥10, in this embodiment Take N=12, P≧10, and take P=50 in this embodiment.
[0039] In this embodiment, in step 1, there are two ways to use each mobile phone to obtain P voice samples corre...