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
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[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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