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.

CN110136746BActive Publication Date: 2021-11-09NINGBO UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Publication Date
2021-11-09

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Abstract

The invention discloses a method for identifying the source of a mobile phone in an additive noise environment based on a fusion feature. The fusion feature composed of the MFCC feature, the STFTSDF feature extracted from the Fourier domain and the CQTSDF feature extracted from the CQT domain is used as the device fingerprint , compared with a single feature, it can more accurately characterize the device distinction information; in the training phase, a multi-scene training method is adopted. In the training set, there are not only clean speech samples without scene noise, but also different scene noise types and noise intensities. The M classification model obtained by training is universal, and can effectively identify the source of mobile phones for speech samples of known noise scenes and unknown noise scenes; it uses the deep learning CNN model to establish the M classification model. , the CNN model not only improves the source recognition accuracy of clean speech samples without adding scene noise, but also greatly improves the mobile phone source recognition effect of noisy speech samples, with strong noise robustness.
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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...

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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...