audio waves energetic attenuation diagram

2 visualizaciones (últimos 30 días)
ting po chun
ting po chun el 11 de En. de 2024
Comentada: ting po chun el 13 de En. de 2024
Hi:
I want to convert audio files into images,please refer to the attached picture.
How can i do it?
Thank!

Respuestas (1)

Ayush Anand
Ayush Anand el 11 de En. de 2024
Hi,
To create a log Power vs. time plot as shown in the picture provided, you could sum the power across all frequencies at each time point to get the total power at that time, and then plot this on a log scale. This could be considered a variant of the common spectogram with frequency domain collapsed, hence the "spectogram" function could be used for the same.
Here's how you can implement this in code:
% Read the Audio File
[audioData, fs] = audioread('sample.wav');
%Since spectogram accepts first argument as vector, ensure audioData is a vector by converting stereo audio to mono if necessary
if size(audioData, 2) == 2
audioData = mean(audioData, 2);
end
% Convert audioData to double if it's not already double
audioData = double(audioData);
% Create the Spectrogram with desired parameters
windowSize = 256; % Window size for the spectrogram
overlap = round(windowSize * 0.75); % Overlap between windows
nfft = 1024; % Number of FFT points
[S, F, T, P] = spectrogram(audioData, windowSize, overlap, nfft, fs);
%Sum the power across all frequencies to get total power at each time point
totalPower = sum(P, 1);
%Create the plot and save it as an image
scatter(T, 10*log10(totalPower));
%... customize the plot
You can refer to the link below to read more on the "spectogram" function:
Hope this helps!
  6 comentarios
ting po chun
ting po chun el 13 de En. de 2024
thank so much!
ting po chun
ting po chun el 13 de En. de 2024
Hi
Did i do something wrong? It seem doens't have two singals
clear
% Read the Audio File
[audioData1, fs] = audioread('聲道式-imp.wav');
%Since spectogram accepts first argument as vector, ensure audioData is a vector by converting stereo audio to mono if necessary
if size(audioData1, 2) == 2
audioData1 = mean(audioData1, 2);
end
% Convert audioData to double if it's not already double
audioData1 = double(audioData1);
% Create the Spectrogram with desired parameters
windowSize = 256; % Window size for the spectrogram
overlap = round(windowSize * 0.75); % Overlap between windows
nfft = 1024; % Number of FFT points
[S, F, T, P1] = spectrogram(audioData1, windowSize, overlap, nfft, fs);
%Sum the power across all frequencies to get total power at each time point
totalPower = sum(P1, 1);
%Create the plot and save it as an image
% scatter(T, 10*log10(totalPower));
%... customize the plot
[audioData2, ~] = audioread('場景式-imp.wav');
if size(audioData2, 2) == 2
audioData2 = mean(audioData2, 2);
end
audioData2 = double(audioData2);
% Create the Spectrogram with desired parameters
windowSize = 256; % Window size for the spectrogram
overlap = round(windowSize * 0.75); % Overlap between windows
nfft = 1024; % Number of FFT points
[S1, F1, T1, P2] = spectrogram(audioData2, windowSize, overlap, nfft, fs);
%Sum the power across all frequencies to get total power at each time point
totalPower1 = sum(P1, 1);
%Create the plot and save it as an image
hold on
scatter(T, 10*log10(totalPower));
scatter(T1, 10*log10(totalPower1));
%... customize the plot
hold off

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