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Merge branch 'main' into alex

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This commit is contained in:
Alex Nguyen 2021-12-08 16:47:15 -08:00
commit 4fd1c6a119
14 changed files with 426 additions and 53 deletions
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DarellsAnnex/app.mlapp
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src/DarellAnnePitchEnvelope.m Normal file
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%Written by Darell and Anne
function output = DarellAnnePitchEnvelope(input, Fs, attack,decay,sustain,release) %percentages for attack, decay, sustain, release
len = length(input);
T = (len-1)/Fs;
attacktime = attack * T * Fs;
decaytime = attacktime + decay * T * Fs;
sustaintime = (T - (release * T)) * Fs;
output = zeros([1,len]);
tcounter = 1;
%attack phase
curr = attacktime;
while tcounter <= curr
ncount = round(curr*log(tcounter)/log(curr)+1);
output(tcounter) = input(ncount);
tcounter = tcounter+1;
end
%decay phase
prevcur = curr;
tcounter = prevcur;
curr = decaytime;
while tcounter <= curr
ncount = round(sustain*curr*(1-log(tcounter)/log(prevcur)) + prevcur);
tcounter = round(tcounter);
output(tcounter)
output(tcounter) = input(ncount);
tcounter = tcounter+1;
end
%sustain phase
prevncount = ncount;
prevcur = curr;
tcounter = prevcur;
curr = sustaintime;
while tcounter <= curr
ncount = round(sustain*(tcounter - prevcur) + prevncount);
tcounter = round(tcounter);
output(tcounter) = input(ncount);
tcounter = tcounter+1;
end
%release phase
prevncount = ncount;
prevcur = curr;
tcounter = prevcur;
curr = Fs;
while tcounter <= Fs
ncount = round(curr*(1-log(tcounter)/log(prevcur)) + prevncount);
tcounter = round(tcounter);
output(tcounter) = input(ncount);
tcounter = tcounter+1;
end
end

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src/FilterSelect.m Normal file
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function output = FilterSelect(input,Fs,LOW,MED,HIGH,number)
if(number == "Option 1")
output = DarellbandpassFilter(input,Fs,LOW,MED,HIGH);
elseif(number == "Option 2")
output = amplifyFreqRange(input, Fs, LOW, MED, HIGH);
else
output = input;
end
end

11
src/Main_test.m
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@ -13,7 +13,7 @@ x = x + generate_sine(amplitude, (frequency+5), phase, fs, duration, duty);
%play over 5 counts, should hear both frequencies, 5 beats per second between the 2 frequencies
playtime = 5;
play_continuous(x, fs, playtime)
%play_continuous(x, fs, playtime)
LOW = 0;
HIGH = frequency + 1;
@ -22,7 +22,14 @@ x = DarellbandpassFilter(x,fs,LOW,MED,HIGH);
%play over 5 counts, should only hear 200hz
playtime = 5;
play_continuous(x, fs, playtime)
%play_continuous(x, fs, playtime)
attack = 0.2;
decay = 0.1;
sustain = 0.8;
release = 0.4;
x = DarellAnnePitchEnvelope(x, Fs, attack,decay,sustain,release);
attack = 0.2;
decay = 0.2;

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src/Petha_Hsu_PitchOffset.m
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% Petha_Hsu_PitchOffset: input a wave and pitch offset (in percentage)
% This function takes a input sound signal and increases the pitch by the
% offset percentage. The output is not 100% accurate. It is only an
% estimation as the information we the function works with is very limited.
% If 100% output is expected, more information like the frequency and type
% of wave would be required. And the estimation only works for
% f_offset > 0.5. Below 0.5, the output is problematic. Again, the output
% is just a good estimation.
% CONTRIBUTORS:
% Pethaperumal Natarajan: I figured a way to increase the pitch of input
% signal by using fourier transform and shifting the frequency using a for
% loop. Then I used inverse transform to get a sound signal back in the time
% domain.
% Wesley Hsu: I helped solve the problem of being unable to lower frequency
% for the loop using the floor function. This allowed rounding to maintain
% the lower signals that were needed when the code returned the signal back
% into the time domain.
function y = Petha_Hsu_PitchOffset(x, f_offset)
len = length(x);
X = fft(x);
X = fftshift(X); %Fourier transform the input wave
Y = zeros(1, len);
midpoint = len/2;
for i = 1:len
%Shifting the Fourier transform in frequency domain to adjust the
%frequency of signal.
%Floor function is used as signals must be integers and not
%doubles.
if floor((i - midpoint) / f_offset + midpoint) < 1 || floor((i - midpoint) / f_offset + midpoint) > len
continue;
end
Y(i) = X(floor((i - midpoint) / f_offset + midpoint));
end
%Plotted graphs to troubleshoot the problem.
%Fs = 44800;
%f = Fs *(-len/2 : len/2 -1) / len;
%tiledlayout(1,3); nexttile;
%plot(f, abs(X)); title("input"); nexttile;
%plot(f, abs(Y)); title("output"); nexttile;
Y = fftshift(Y);
y = ifft(Y);
y = real(y);
% Petha_Hsu_PitchOffset: input a wave and pitch offset (in percentage)
% This function takes a input sound signal and increases the pitch by the
% offset percentage. The output is not 100% accurate. It is only an
% estimation as the information we the function works with is very limited.
% If 100% output is expected, more information like the frequency and type
% of wave would be required. And the estimation only works for
% f_offset > 0.5. Below 0.5, the output is problematic. Again, the output
% is just a good estimation.
% CONTRIBUTORS:
% Pethaperumal Natarajan: I figured a way to increase the pitch of input
% signal by using fourier transform and shifting the frequency using a for
% loop. Then I used inverse transform to get a sound signal back in the time
% domain.
% Wesley Hsu: I helped solve the problem of being unable to lower frequency
% for the loop using the floor function. This allowed rounding to maintain
% the lower signals that were needed when the code returned the signal back
% into the time domain.
function y = Petha_Hsu_PitchOffset(x, f_offset)
len = length(x);
X = fft(x);
X = fftshift(X); %Fourier transform the input wave
Y = zeros(1, len);
midpoint = len/2;
for i = 1:len
%Shifting the Fourier transform in frequency domain to adjust the
%frequency of signal.
%Floor function is used as signals must be integers and not
%doubles.
if floor((i - midpoint) / f_offset + midpoint) < 1 || floor((i - midpoint) / f_offset + midpoint) > len
continue;
end
Y(i) = X(floor((i - midpoint) / f_offset + midpoint));
end
%Plotted graphs to troubleshoot the problem.
%Fs = 44800;
%f = Fs *(-len/2 : len/2 -1) / len;
%tiledlayout(1,3); nexttile;
%plot(f, abs(X)); title("input"); nexttile;
%plot(f, abs(Y)); title("output"); nexttile;
Y = fftshift(Y);
y = ifft(Y);
y = real(y);
end

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src/PitchEnvelopeSelect.m
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@ -1,6 +1,6 @@
function output = PitchEnvelopeSelect(input, Fs, attack,decay,sustain,release,number)
if(number == "Option 1")
output = DarellAmplitudeEnvelope(input, Fs, attack,decay,sustain,release);
output = DarellAnnePitchEnvelope(input, Fs, attack,decay,sustain,release);
else
output = input;
end

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src/SoundGeneratorSelect.m
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@ -5,7 +5,10 @@ function output = SoundGeneratorSelect(amplitude, frequency, phase, fs, duration
output = generate_square(amplitude, frequency, phase, fs, duration, duty);
elseif(number == "Option 3")
output = generate_triangle(amplitude, frequency, phase, fs, duration, duty);
elseif(number == "Option 4")
output = generate_sawtooth(amplitude, frequency, phase, fs, duration, duty);
elseif(number == "Option 5")
output = generate_white(amplitude, frequency, phase, fs, duration, duty);
else
output = 0;
end

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src/bandreject_filter.m Normal file
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function output_y = bandreject_filter(Input, Fs, Low, High)
% A filter that lets through most frequencies unaltered
% but attentuates the frequencies in the specified range to
% very low levels
% (basically exliminates them)
% By Yalu Ouyang
% Input: the input signal in the time domain
% Fs: the sampling frequency
% Low: the lower limit of the specified range
% High: the upper limit of the specified range
% Returns Output: the filtered signal in the time domain
len = length(Input);
F = Fs * (-len/2 : (len/2 - 1)) / len ;
% modified signal in the frequency domain
% using Fourier Transform
mod_freq = fftshift(fft(Input));
len_f = length(mod_freq);
% use this array to record the frequencies
% that should pass through
% 0 indicates reject
% 1 indicates pass
multiplier = zeros([1,len_f]);
for index = 1 : len_f
% within range of band reject
% so elminate these frequencies
if ((Low < abs(F(index))) && (abs(F(index)) < High))
multiplier(index) = 0;
% outside of specified range
% so shoudln't be altered
else
multiplier(index) = 1;
end
end
% filtered signal in the frequency domain
filtered_mod_freq = fftshift(mod_freq .* multiplier);
% convert signal back to the time domain
Output = real(ifft(filtered_mod_freq));
end
% This function is useful for eliminating
% unwanted signals that have frequencies close to the
% median frequency of the original signal
% (consider overall frequencies as one part,
% this elminates the middle portion)
% Fourier transform is applied in this function
% to make it easier to eliminate specified
% frequencies of the signal
% (easier to do so in the frequency domain)

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src/epic_effect_schluep.m Normal file
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function output = epic_effect_schluep(input, Fs, LOW, MED, HIGH)
% epic_effect_schluep: Outputs a more "epic" version of the input sound.
% This is done by amplifying low frequencies and by implementing a chorus
% effect. A chorus effect is created when multiple copies of sound delayed
% by a small, random amount are added to the original signal. Works best on
% songs with a stronger bassline.
% Try this function out with "Strong_Bassline.mp3".
% CONTRIBUTORS:
% Nicolas Schluep: Function Author
% DOCUMENTATION:
% input: The input sound in the time-domain.
% Fs: The sampling rate of the input signal. A typical value is 44100 Hz.
% HIGH: The maximum frequency the filter will amplify. A typical value for
% this variable is 1000 Hz.
non_stereophonic = input(:, 1); % Removes the sterophonic property of the input sound
% by just taking the first column of data.
Len = length(non_stereophonic);
F = Fs * ((-Len/2) : ((Len/2) - 1)) / Len; % Creating the array of frequencies
% which the FFT Shifted version of the signal can be plotted against.
inputFreq = fftshift(fft(non_stereophonic)); % Creates the Fourier Transform of the
% input signal. fftshift() makes it such that the zero frequency is at the
% center of the array.
lowAmplifyFilter = zeros(1, length(inputFreq));
% Creating a filter which amplifies lower frequencies.
for i = 1:length(lowAmplifyFilter)
if abs(F(i)) < HIGH
lowAmplifyFilter(i) = 1.25;
else
lowAmplifyFilter(i) = 1.00;
end
end
lowPassedInput = inputFreq .* transpose(lowAmplifyFilter); %Apply the "lowAmplifyFilter".
% Adding the chorus effect.
realOutput = real(ifft(fftshift(lowPassedInput)));
output = realOutput;
% Adding 100 randomly delayed signals to the original signal which creates the chorus effect.
for i = 1:100
currentDelay = 0.003 * rand(); % The current delay of the sound in seconds.
currentIndex = round(currentDelay * Fs); % Find the first index where the sound should start playing.
delayedOutput = [zeros(currentIndex, 1); realOutput]; % Adds "currentIndex" zeros to the front of the
% "realOutput" vector to create a slightly delayed version of the signal.
delayedOutput = delayedOutput(1:length(realOutput)); % Truncates the "delayedOutput"
% vector so that it can be added to the "realOutput" vector.
output = output + delayedOutput;
end
output = output ./ 100; % Divide by 100 to decrease the amplitude of the sound to a normal level.

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src/fade_in.m Normal file
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function output = fade_in(input, time)
% Creates a fade-in sound effect that lasts a given
% time parameter of the input sound signal
% By Yalu Ouyang
% input: a 1D array that represents the sound signal in the time domain
% time: how long the fade in effect should last
% Shouldn't be longer than the input signal (in which case the function
% treats it as the duration of the signal)
% Returns modified signal in the time domain (output).
len = length(input);
% if time parameter longer than signal, treat time as
% the duration of original signal
if time > len
time = len
end
% set multiplier as 1D array
% fade in effect: from no volume to full volume of signal
multiplier = (1 : time) / time;
% the resulting fade-in output
output = input .* multiplier;
end
% This is useful for making videos, specifically the intro part

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src/fade_out.m Normal file
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function output = fade_out(input, time)
% Creates a fade-out sound effect that lasts a given
% time parameter of the input sound signal
% By Yalu Ouyang
% input: a 1D array that represents the sound signal in the time domain
% time: how long the fade out effect should last
% Shouldn't be longer than the input signal
% (in which case the function treats it as the duration of the signal)
% Returns modified signal in the time domain (output).
len = length(input);
% if time parameter longer than signal, treat time as
% the duration of original signal
if time > len
time = len
end
% set multiplier as 1D array
multiplier = (1 : time) / time;
% fade out effect: from full volume of signal to no volume
multiplier = flip(multiplier)
% the resulting fade-in output
output = input .* multiplier;
end
% This is useful for creating videos, specifically the outro part

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src/muffled_effect_schluep.m Normal file
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function output = muffled_effect_schluep(input, Fs, LOW, MED, HIGH)
% muffled_effect_schluep: Outputs a muffled version of the the original input
% sound in the time domain. This makes it sound as if the audio is being
% played in another room.
% Try this function out with "Strong_Bassline.mp3".
% CONTRIBUTORS:
% Nicolas Schluep: Function Author
% DOCUMENTATION:
% input: The input sound in the time-domain.
% Fs: The sampling rate of the input signal. A typical value is 44100 Hz.
% HIGH: The maximum frequency that the low-pass filter will let pass. A
% typical value for this variable is 1000 Hz.
non_stereophonic = input(:, 1); % Removes the sterophonic property of the input sound
% by just taking the first column of data.
Len = length(non_stereophonic);
F = Fs * ((-Len/2) : ((Len/2) - 1)) / Len; % Creating the array of frequencies
% which the FFT Shifted version of the signal can be plotted against.
inputFreq = fftshift(fft(non_stereophonic)); % Creates the Fourier Transform of the
% input signal. fftshift() makes it such that the zero frequency is at the
% center of the array.
lowPassFilter = zeros(1, length(inputFreq));
% Creating Low Pass Filter
for i = 1:length(lowPassFilter)
if abs(F(i)) < HIGH
lowPassFilter(i) = 1;
else
lowPassFilter(i) = 0;
end
end
lowPassedInput = inputFreq .* transpose(lowPassFilter); %Apply the low-pass filter.
% Adding a slight reverb effect.
realOutput = real(ifft(fftshift(lowPassedInput)));
delay = 0.001; % The delay of the sound in seconds.
index = round(delay*Fs); % Find the first index where sound should start playing
% by multiplying the delay by the sampling frequency.
delayedOutput = [zeros(index, 1); realOutput]; % Adds "index" zeros to the front of the
% "realOutput" vector to create a slightly delayed version of the signal.
delayedOutput = delayedOutput(1:length(realOutput)); % Truncates the "delayedOutput"
% vector so that it can be added to the "realOutput" vector.
output = (realOutput + delayedOutput) ./ 2.0; % Adds the "realOutput" and "delayedOutput"
% vectors to create a reverb effect. Divides by 2 to avoid clipping
% effects.

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src/seperate_prevalent_schluep.m Normal file
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function output = seperate_prevalent_schluep(input, Fs, LOW, MED, HIGH)
% seperate_prevalent_schluep: Attempts to seperate the most prevalent frequencies
% from the input sound by finding the most prevalent frequencies and applying
% a band-pass filter to a small region around those frequencies.
% Try this function out with "Strong_Bassline.mp3".
% CONTRIBUTORS:
% Nicolas Schluep: Function Author
% DOCUMENTATION:
% input: The input sound in the time-domain.
% Fs: The sampling rate of the input signal. A typical value is 44100 Hz.
% HIGH: The maximum distance around the maximum frequency value that will
% not be attenuated. A good range of values is usually 250-500 Hz, but it
% depends on the input sound.
non_stereophonic = input(:, 1); % Removes the sterophonic property of the input sound
% by just taking the first column of data.
Len = length(non_stereophonic);
F = Fs * ((-Len/2) : ((Len/2) - 1)) / Len; % Creating the array of frequencies
% which the FFT Shifted version of the signal can be plotted against.
inputFreq = fftshift(fft(non_stereophonic)); % Creates the Fourier Transform of the
% input signal. fftshift() makes it such that the zero frequency is at the
% center of the array.
bandPassFilter = zeros(1, length(inputFreq));
maxAmplitude = 0;
mostPrevalentFrequency = 0;
% Finding the most prevalent frequency.
for i = round(length(inputFreq)/2):length(inputFreq)
if inputFreq(i) > maxAmplitude
maxAmplitude = inputFreq(i);
mostPrevalentFrequency = F(i);
end
end
% Determining maximum and minimum frequency values for the Band Pass filter.
maxFrequency = mostPrevalentFrequency + HIGH;
minFrequency = mostPrevalentFrequency - HIGH;
if minFrequency < 0.0
minFrequency = 0.0;
end
% Creating the Band-Pass filter.
for i = 1:length(bandPassFilter)
if (abs(F(i)) < maxFrequency) && (abs(F(i)) > minFrequency)
bandPassFilter(i) = 1;
else
bandPassFilter(i) = 0;
end
end
bandPassedInput = inputFreq .* transpose(bandPassFilter); %Apply the Band-Pass Filter.
output = real(ifft(fftshift(bandPassedInput)));