I. Introduction to Voice encryption (with course Assignment Report)
Speech signal processing is a new subject of speech signal processing with digital signal processing technology and phonetics knowledge. Information transmission through speech is the most important, most effective, most common and most convenient form of information exchange. Voice encryption is also important. Matlab language is a kind of data analysis and processing function is very powerful computer application software, its signal processing and analysis toolbox for speech signal analysis provides very rich functions. Through MATLAB AM modulation and demodulation of the voice signal, the encryption and decryption of the voice signal is realized.
Two, some source code
[y,fs]=audioread('a.wav'); % Voice signal acquisition n1=length (y); % The length of speech signal Y= FFT (Y,n1); The Fourier transform f is equal to8000000; % carrier frequency M=size(y); t=0:1:M- 1;
s=sin(f*2*3.14*t); % Construct carrier sequence s=s'; C =[s,s]; A0=1; A=ones(M); % Construct dc component y1=(y+A).*c; % synchronous modulation, encrypt the signal n2=length(y1); Y1=fft(y1,n2); % Fourier transform n3=length(y2); Y2=fft(y2,n3); Ft=8000;
Fp=1000;
Fs=1200;
wp=2*pi*Fp/Ft;
ws=2*pi*Fs/Ft;
fp=2*Ft*tan(wp/2);
fs=2*Fs*tan(wp/2);
figure;
subplot(2.1.1);
plot(z11);
subplot(2.1.2);
figure;
subplot(3.2.1);
plot(y);
title('Original signal waveform');
subplot(3.2.2);
plot(abs(Y)); title('Raw signal spectrum');
subplot(3.2.3);
plot(y1);
title('Encrypted signal waveform');
subplot(3.2.4);
plot(abs(Y1));
title('Encrypted signal Spectrum');
subplot(3.2.5);
plot(y3);
title('Decrypted signal waveform'); n4=length(y3); Y3=fft(y3,n4); % Fourier transform subplot(3.2.6);
plot(abs(Y3));
title('Decrypted signal spectrum');
wavwrite(y3, 'decryption. Wav'); % Decrypted audio signal named "decrypt.wav"Copy the code
3. Operation results
Matlab version and references
1 matlab version 2014A
[1] Han Jiqing, Zhang Lei, Zheng Tieran. Speech Signal Processing (3rd edition) [M]. Tsinghua University Press, 2019. [2] LIU Ruobian. Deep Learning: Practice of Speech Recognition Technology [M]. Tsinghua University Press, 2019.