Can Anyone help me to remove noise from this audio file in matlab

I am new to matlab. Can anyone please help me remove noise from this audio signal. This is for a college assignment. the audio file is attached here. Thank you.

[Jan]

Because this is a homework question, you will get an answer if you show your own effort and ask a specific question.

[puneet lalwani]

I tried using cheby2 filter but the thing is I cannot make out at what range is the noise. I cannot remove the noise from this. The code i used is given below

%%1) Load the 'audio_sample.wav' file in MATLAB

[sample_data, sample_rate] = audioread('aat_audio.mp3');

% a. Plot the signal in time and the amplitude of its frequency

% components using the FFT.

sample_period = 1/sample_rate;

t = (0:sample_period:(length(sample_data)-1)/sample_rate);

subplot(2,2,1)

plot(t,sample_data)

title('Time Domain Representation - Unfiltered Sound')

xlabel('Time (seconds)')

ylabel('Amplitude')

xlim([0 t(end)])

fs = sample_rate/2;

m = length(sample_data); % Original sample length.

n = pow2(nextpow2(m)); % Transforming the length so that the number of

% samples is a power of 2. This can make the transform computation

% significantly faster,particularly for sample sizes with large prime

% factors.

y = fft(sample_data, n);

f = (0:n-1)*(sample_rate/n);

amplitude = abs(y)/n;

subplot(2,2,2)

plot(f(1:floor(n/2)),amplitude(1:floor(n/2)))

title('Frequency Domain Representation - Unfiltered Sound')

xlabel('Frequency')

ylabel('Amplitude')

% b. Listen to the audio file.

% sound(sample_data, sample_rate)

%%2) Filter the audio sample data to remove noise from the signal.

order = 7;

%%[n,Ws] = cheb2ord(2000/fs,2020/fs,1,100); % Filter Order

[z,p,k] = cheby2(order,150,0.4,'low'); % Filter Design

[soslp,glp] = zp2sos(z,p,k);

%%[b,a] = butter(order,1000/(sample_rate/2),'low');

filtered_sound = filtfilt(soslp, glp, sample_data);

%%filtered_sound = filter(b,a,sample_data);

sound(filtered_sound, sample_rate)

t1 = (0:sample_period:(length(filtered_sound)-1)/sample_rate);

subplot(2,2,3)

plot(t1,filtered_sound)

title('Time Domain Representation - Filtered Sound')

xlabel('Time (seconds)')

ylabel('Amplitude')

xlim([0 t1(end)])

m1 = length(sample_data); % Original sample length.

n1 = pow2(nextpow2(m1)); % Transforming the length so that the number of

% samples is a power of 2. This can make the transform computation

% significantly faster,particularly for sample sizes with large prime

% factors.

y1 = fft(filtered_sound, n1);

f = (0:n1-1)*(sample_rate/n1);

amplitude = abs(y1)/n1;

subplot(2,2,4)

plot(f(1:floor(n1/2)),amplitude(1:floor(n1/2)))

title('Frequency Domain Representation - Filtered Sound')

xlabel('Frequency')

ylabel('Amplitude')