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== 1.Introduction ==
 
== 1.Introduction ==
In this section, you will learn how to use the signal processing technique in Matlab to add several sound effects to music. I will introduce three basic sound effects, namely, echo, flanger and chorus.
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Sound effects as echo, flanger and chorus are largely implemented in sound productions. In this section, you will learn the fundamental ideas of each sound effect and use the signal processing technique in Matlab to create these sound effect to your music.
 
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== 2.Echo effect ==  
 
== 2.Echo effect ==  
The fundamental theory behind the echo effect is that the original music signal combines with its repeated signal with a fixed delay period. This effect can be achieved by implementing a comb filter. The difference equation for this simple comb filter can be written as follows:
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The echo effect can be simply considered as a delay of music signal. It is produced by repeating the original music signal after a fixed amount of time period. This effect is extremely applied in microphones and stereos. A FIR filter with a single delay will achieve this effect. The difference equation for the FIR filter can be written as follows:
 
   Y[n] = X[n] + a * X[n – D]
 
   Y[n] = X[n] + a * X[n – D]
 
Where:
 
Where:
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Y[n]: output signal
 
Y[n]: output signal
  
D :  number of samples during delay
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D :  number of samples during delay, fixed value
  
 
a :  attenuation coefficient.  |a| < 1
 
a :  attenuation coefficient.  |a| < 1
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== 3.Flanger effect ==
 
== 3.Flanger effect ==
The flanging effect is produced by mixing two identical music signals with a varying delay function. Unlike the fixed delay D in the comb filter, the flanger filter has a non-constant delay D, which changes periodically. The difference equation for this simple comb filter can be written as follows:
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The flanging effect is produced by mixing two identical music signals with a varying delay function. Unlike the fixed delay D in the echo effect design, the flanger filter has a non-constant delay D, which changes periodically. The difference equation for this flanger filter can be written as follows:
                                  Y[n] = X[n] + a * X[ n – D[n] ]
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                        Y[n] = X[n] + a * X[ n – D[n] ]
 +
 
 +
Where:
 +
 
 +
X[n] : input signal
 +
 
 +
Y[n]: output signal
 +
 
 +
D :  periodic delay function
 +
 
 +
a :  attenuation coefficient.  |a| < 1
  
 
==== % Matlab code: ====
 
==== % Matlab code: ====
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end
 
end
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 +
Examples:

Revision as of 21:51, 29 November 2015

1.Introduction

Sound effects as echo, flanger and chorus are largely implemented in sound productions. In this section, you will learn the fundamental ideas of each sound effect and use the signal processing technique in Matlab to create these sound effect to your music.

2.Echo effect

The echo effect can be simply considered as a delay of music signal. It is produced by repeating the original music signal after a fixed amount of time period. This effect is extremely applied in microphones and stereos. A FIR filter with a single delay will achieve this effect. The difference equation for the FIR filter can be written as follows:

  			Y[n] = X[n] + a * X[n – D]

Where:

X[n] : input signal

Y[n]: output signal

D : number of samples during delay, fixed value

a : attenuation coefficient. |a| < 1


% Matlab code

[x,fs] = wavread(‘singsing.wav’);  % load the music and get the sampling frequency

length = size(x);  % get the length of the music file

a = 0.3;  % set the attenuation factor

delay = 0.38;

D = delay*fs;  % set the delay time in s

y = zeros(length);  % initialize the output music signal

for i = D + 1 : 1 : length;

	y(i) = x(i) + a*x(i-D);

end;

sound(y, fs);  % play the echo


Example:


3.Flanger effect

The flanging effect is produced by mixing two identical music signals with a varying delay function. Unlike the fixed delay D in the echo effect design, the flanger filter has a non-constant delay D, which changes periodically. The difference equation for this flanger filter can be written as follows:

                       Y[n] = X[n] + a * X[ n – D[n] ]

Where:

X[n] : input signal

Y[n]: output signal

D : periodic delay function

a : attenuation coefficient. |a| < 1

% Matlab code:

[y, fs, nbits] = wavread(file);  %Reading the file

low_n = round(0.0*fs);  %Creating the vector according to which delay is varied

high_n = round(0.0057*fs);

delay_vary_p = 8;

delay_step = (delay_vary_p/4)/(1/fs);

delay_1 = round(linspace(low_n,high_n,delay_step));

delay_2 = round(linspace(high_n,low_n,delay_step));

delay = [delay_1 delay_2];

no_points = length(y(:,1));

n_rep = round(no_points/length(delay));

delay = repmat(delay,1,n_rep);

delay = [delay delay(1:no_points-length(delay))];

out_wav(:,1) = zeros(1,no_points);

out_wav(:,2) = zeros(1,no_points);

for i=1:no_points

   n = i-delay(i);
   if n>0
       out_wav(i,1) = y(i,1)+y(n,1);
       out_wav(i,2) = y(i,2)+y(n,2);
   else
       out_wav(i,1) = y(i,1);
       out_wav(i,2) = y(i,2);
   end

end

Examples:

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