I am new to matlab and I'm trying to filter the noise out of the audio. I tried some filters but can't event get close to lessening the noise.

Question

Godwin Emmanuel 2024-4-28

0
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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2112516-i-am-new-to-matlab-and-i-m-trying-to-filter-the-noise-out-of-the-audio-i-tried-some-filters-but-can

评论： Star Strider 2024-4-28

采纳的回答： Star Strider

[originalAudio, Fs] = audioread('original.wav');

[noisyAudio, ~] = audioread('noisy.wav');

t = (0:length(originalAudio)-1)/Fs;

figure;

subplot(2,1,1);

plot(t, originalAudio);

xlabel('Time (s)');

ylabel('Amplitude');

title('Original Audio');

subplot(2,1,2);

plot(t, noisyAudio);

xlabel('Time (s)');

ylabel('Amplitude');

title('Noisy Audio');

N = length(originalAudio);

f = Fs*(0:(N/2))/N;

originalSpec = fft(originalAudio);

noisySpec = fft(noisyAudio);

figure;

subplot(2,1,1);

plot(f, abs(originalSpec(1:N/2+1)));

xlabel('Frequency (Hz)');

ylabel('Magnitude');

title('Original Audio Spectrum');

subplot(2,1,2);

plot(f, abs(noisySpec(1:N/2+1)));

xlabel('Frequency (Hz)');

ylabel('Magnitude');

title('Noisy Audio Spectrum');

fc1 = 2000;

fc2 = 500;

[b1, a1] = butter(6, fc1/(Fs/2), 'low');

[b2, a2] = butter(6, fc2/(Fs/2), 'low');

filteredAudio1 = filter(b1, a1, noisyAudio);

filteredAudio2 = filter(b2, a2, filteredAudio1);

figure;

plot(t, filteredAudio2);

xlabel('Time (s)');

ylabel('Amplitude');

title('Filtered Audio');

filteredSpec2 = fft(filteredAudio2);

figure;

plot(f, abs(filteredSpec2(1:N/2+1)));

xlabel('Frequency (Hz)');

ylabel('Magnitude');

title('Filtered Audio Spectrum');

figure;

subplot(2,1,1);

plot(t, originalAudio);

xlabel('Time (s)');

ylabel('Amplitude');

title('Original Audio');

subplot(2,1,2);

plot(t, filteredAudio2);

xlabel('Time (s)');

ylabel('Amplitude');

title('Filtered Audio (Closest to Original)');

sound(filteredAudio2, Fs);

I have the noisy file and the original file that is attached: I need to make the noisy file as close to the original as possible.

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Godwin Emmanuel 2024-4-28

Thank you!

Star Strider 2024-4-28

My pleasure!

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Answer 1

Star Strider 2024-4-28

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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2112516-i-am-new-to-matlab-and-i-m-trying-to-filter-the-noise-out-of-the-audio-i-tried-some-filters-but-can#answer_1449096

编辑：Star Strider 2024-4-28

在 MATLAB Online 中打开

Wavfiles.zip

If it contains broadband noise, a frequency-selective filter will not be able to eliminate the noise. In that event, experiment with either wavelet denoising or use the sgolayfilt function. The Savitzky-Golay filter is usually effective at eliminating broadband noise, although it requires experimentation. I usually use a 3-degree polynomial and then change the ‘framelen’ value until I get the result I want.

EDIT — (28 Apr 2024 at 15:15)

The ‘noisy’ file definitely has broadband noise, however it may not be possible to filter it back to the original file.

Uz = unzip('Wavfiles.zip')

Uz = 1x3 cell array

{'Wavfiles/'} {'Wavfiles/noisy.wav'} {'Wavfiles/original.wav'}

figure

tiledlayout(4,1)

for k = 1:2

fn = Uz{k+1}

[y{k},Fs(k)] = audioread(fn);

ysize = size(y{k},1);

t{k} = linspace(0, ysize-1, ysize).'/Fs(k);

nexttile

plot(t{k}, y{k})

grid

xlabel('Time')

ylabel('Amplitude')

title(fn)

[FTs1{k},Fv{k}] = FFT1(y{k},t{k});

nexttile

plot(Fv{k}, abs(FTs1{k}))

grid

xlabel('Frequency')

ylabel('Magnitude')

title(fn)

end

fn = 'Wavfiles/noisy.wav'

fn = 'Wavfiles/original.wav'

y1_filt = sgolayfilt(y{1}, 3, 201);

figure

tiledlayout(2,1)

nexttile

plot(t{1}, y{1})

grid

xlabel('Time')

ylabel('Amplitude')

title('Unfiltered')

nexttile

plot(t{2}, y1_filt)

grid

xlabel('Time')

ylabel('Amplitude')

title('Filtered')

function [FTs1,Fv] = FFT1(s,t)

t = t(:);

L = numel(t);

if size(s,2) == L

s = s.';

end

Fs = 1/mean(diff(t));

Fn = Fs/2;

NFFT = 2^nextpow2(L);

FTs = fft((s - mean(s)) .* hann(L).*ones(1,size(s,2)), NFFT)/sum(hann(L));

Fv = Fs*(0:(NFFT/2))/NFFT;

% Fv = linspace(0, 1, NFFT/2+1)*Fn;

Iv = 1:numel(Fv);

FTs1 = FTs(Iv,:);

end

I will consider other possibilities, however this is likely the best I can do with this file. The noise completely swamps the signal.

.

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Godwin Emmanuel 2024-4-28

Btw I edited the file to this

% Unzip the files

try

Uz = unzip('Wavfiles.zip');

catch

error('Failed to unzip the file. Make sure "Wavfiles.zip" exists in the current directory.');

end

% Check if any files were extracted

if isempty(Uz)

error('No files were extracted from the ZIP archive.');

end

% Initialize variables

y = cell(1, 2);

Fs = zeros(1, 2);

t = cell(1, 2);

FTs1 = cell(1, 2);

Fv = cell(1, 2);

% Plotting and analyzing audio files

for k = 1:min(2, numel(Uz)-1)

try

fn = Uz{k+1};

[y{k}, Fs(k)] = audioread(fn);

ysize = size(y{k}, 1);

t{k} = linspace(0, ysize-1, ysize) / Fs(k);

figure;

tiledlayout(2, 1);

% Plot original waveform

nexttile;

plot(t{k}, y{k});

grid on;

xlabel('Time');

ylabel('Amplitude');

title(['Original Audio - ', fn]);

% Calculate and plot frequency spectrum

[FTs1{k}, Fv{k}] = FFT1(y{k}, t{k});

nexttile;

plot(Fv{k}, abs(FTs1{k}));

grid on;

xlabel('Frequency');

ylabel('Magnitude');

title(['Frequency Spectrum - ', fn]);

catch

warning(['Error processing file ', fn]);

end

% Smoothing the first audio file

try

y1_filt = sgolayfilt(y{1}, 3, 201);

% Normalize the filtered audio to [-1, 1] range

y1_filt_normalized = y1_filt / max(abs(y1_filt));

filtered_filename = 'filtered_audio.wav'; % Define the filename for the filtered audio

audiowrite(filtered_filename, y1_filt_normalized, Fs(1)); % Save the filtered audio

catch

warning('Error smoothing the first audio file.');

y1_filt_normalized = [];

filtered_filename = '';

end

% Plot unfiltered and filtered audio

figure;

tiledlayout(2, 1);

try

% Plot unfiltered audio

nexttile;

plot(t{1}, y{1});

grid on;

xlabel('Time');

ylabel('Amplitude');

title('Unfiltered Audio');

% Plot filtered audio

nexttile;

if ~isempty(y1_filt_normalized)

plot(t{1}, y1_filt_normalized);

grid on;

xlabel('Time');

ylabel('Amplitude');

title('Filtered Audio');

else

warning('Filtered audio is empty.');

end

catch

warning('Error plotting audio.');

end

function [FTs1, Fv] = FFT1(s, t)

try

t = t(:);

L = numel(t);

if size(s, 2) == L

s = s.';

end

Fs = 1 / mean(diff(t));

Fn = Fs / 2;

NFFT = 2^nextpow2(L);

FTs = fft((s - mean(s)) .* hann(L), NFFT) / sum(hann(L));

Fv = Fs * (0:(NFFT/2)) / NFFT;

Iv = 1:numel(Fv);

FTs1 = FTs(Iv,:);

catch

error('Error in FFT calculation.');

end

Sam Chak 2024-4-28

In practice, what reliable options do we have to attenuate the effect of broadband noise before it corrupts the original audio during measurement? Restoring the original audio from the noise-corrupted audio seems like a challenging task, although I acknowledge that noise-corrupted audio is still audible to humans to a certain extent.

If we train an AI Voice Classifier using the original audio, do you think it would be capable of improving the intelligibility of the audio by reconstructing certain parts of the signal?

Star Strider 2024-4-28

@Godwin Emmanuel — Thank you!

@Sam Chak — That could work. I don’t have sufficient experience with A.I. audio processing to attempt it. I am not certain how to approach this problem from that perspective, however I would definitely like to find out how to do it.

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