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Multi-model ID recognition method based on scoring difference weight compromised

An identity recognition and multi-modal technology, applied in character and pattern recognition, instruments, computer components, etc., can solve problems such as failure to achieve fusion effects and performance impact of classifiers, achieve extensive security and adaptability, and overcome inadequacy Integrity, Uncertainty Reduction Effects

Inactive Publication Date: 2008-01-23
ZHEJIANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The fusion method with fixed parameters will largely affect the performance due to the pairwise effect of the classifiers.
However, the quality and size of the training set make the decision-level fusion method of parameter training often unable to achieve the theoretical fusion effect.

Method used

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  • Multi-model ID recognition method based on scoring difference weight compromised
  • Multi-model ID recognition method based on scoring difference weight compromised
  • Multi-model ID recognition method based on scoring difference weight compromised

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Embodiment Construction

[0012] The present invention will be further introduced below in conjunction with accompanying drawing and embodiment: the method of the present invention is divided into three steps altogether.

[0013] The first step, voiceprint recognition

[0014] Speaker recognition is divided into four parts: speech preprocessing, feature extraction, model training, and recognition.

[0015] 1. Speech preprocessing

[0016] Speech preprocessing is divided into three parts: sampling and quantization, de-zero drift, pre-emphasis and windowing.

[0017] A), sampling quantization

[0018] I. Filter the audio signal with a sharp cut-off filter to make its Nyquist frequency F N 4KHZ;

[0019] II. Set audio sampling rate F=2F N ;

[0020] III. For audio signals a (t) Sampling by period to obtain the amplitude sequence of the digital audio signal s ( n ) = s a ( ...

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Abstract

This invention relates to a weight combined multi-mode identity identification method based on score difference, which first of all utilizes a group of sample data of speakers and the score of each speaker model in each sample templet of a traditional mono-mode sorter to record the score difference of two speakers if the model and the sample got the maximum score belongs to different speakers then accumulates all these differences in the single sorters to decide the weight of each mode by the score differences of the sorters. The effectiveness is: carrying out cross identity identification by multiple biology properties and applying an amendatory weight algorithm SDWS based on the score difference to combine two biological identification modes and integrate the results of the identification.

Description

technical field [0001] The invention relates to classifier fusion technology, and mainly relates to a multimodal identity recognition method based on score difference weighted fusion. Background technique [0002] In real-life applications, identity authentication is a very complex task, because it needs to achieve high performance and requires strong robustness. Biometric authentication technology uses people's own physical characteristics as the basis for identity authentication, which is fundamentally different from traditional authentication technologies based on "what you have" or "what you know", and truly uses people themselves as the basis for identity authentication , who truly represent themselves. [0003] Among the numerous biometric authentication technologies, identity authentication based on voice and image are two popular methods at present. Voiceprint recognition, that is, speaker recognition, has the advantages of no loss, no memory, easy to use, economic...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00
Inventor 吴朝晖杨莹春李东东
Owner ZHEJIANG UNIV
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