| In recent years, biometrics recognition technique is more and more used in persons' identity recognition for its great security. Biology recognition technique, which can not be copied, is a solution scheme to validate identity by using the physiology and the action character of human self. Biology character of human includes dactylogram, voice, face, retina, iris, palm form, palm vein, skeletal framework and so on. The core of the biology recognition is how to get those biology characters and how to adjudge by the standard.Voice is the basic instrumentality of the human's information communication. Voice signal is the individual inherence character. The voice processing technique has taken a huge progress with information science technique's improvement.The voice signal processing technique has some branches — Voice Recognition, Voice Compound, Voice Coding, and so on. VR has two aspects: Speaker Recognition and Voice Content Recognition. SR analyses the individual character of the speaker's voice, and then finds which that speaker is. What it emphasized is a characteristic difference of the voice's signal itself between different people. Speaker recognition also has two aspects: Speaker SI(Speaker Identification)and SV(Speaker Verification).The former judges that a certain voice sample waiting to be discerned is whose voice in the voice database; the latter judges that the speaker " is or not is" the voice of a certain specific one a piece of waiting to be discerned. Its output has only two kinds of results (the only two results of whether the speaker is or not.).The forming process of the voice is closely related to sport of the vocal organs. The physics sports of vocal organs are more slowly compared with voice frequency. So voice signals can often be assumed steady in a very short time. Various kinds of arithmetic of voice recognition are because of this kind of assumption.This paper developed an embedded text-independent voice door manager system based on the research of voice recognition technique. This system is written by C, makes it better portability. According to the characters of the door manager system , this system adopted Speaker Verification of Speaker recognition. The main flow of this system includes pretreatment, acoustics parameter analyzing and characteristic draw, mode forming, measure estimate, adjudge, and so on.The pretreatment includes: Sample and quantization, aggravate in advance and filtrating wave, adding window and dividing into frame, calculating parameters of time field and frequency field, extreme point measuring etc. This system utilizing pairs of buffer technology gather voice sample in real time, 8000 times samples per second. Samples then pass a one rank high-pass filter 9375 z - 1, namely aggravate filter in advance. The purposes of it lie in excepting that low frequency interference, promoting frequency spectrums of part, dispelling direct current drift, and suppressing the result of the noise at random. Adding window and dividing into frame, every 240 samples are combined to one frame. The frame is moved for 80 for sample array, then calculates the rate out of zero and energy parameter at every frame, and carries on extreme point measure according to experience threshold value.Now, LPCC parameter and MFCC parameter are mostly used as the characteristic parameter in voice recognition method. To speaker recognition, MFCC parameter loads more individual character characteristic, so this system has adopted MFCC parameter as the characteristic parameter. According the result of the experiment, one rank difference parameter of MFCC embodies the forward-and-back voice frame's characteristic more when text-dependent. So this system didn't adopt the one rank difference parameter, distilled the MFCC parameter at 16 dimensions for every frame only, and got the parameter array.This system adopted Hidden Markov Model (HMM) for speaker to train the template. The application of HMM is the most important achievement that the voice recognition field has been ma...
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