spectrogram

I generated spectrogram of a "seven" utterance using the "egs/tidigits" code from Kaldi, using 23 bins, 20kHz sampling rate, 25ms window, and 10ms shift. Spectrogram appears as below visualized via MATLAB imagesc function: I am experimenting with using Librosa as an alternative to Kaldi. I set up my code as below using the same number of bins, sampling rate, and window length / shift as above. time_series, sample_rate = librosa.core.load("7a.wav",sr=20000) spectrogram = librosa.feature.melspectrogram(time_series, sr=20000, n_mels=23, n_fft=500, hop_length=200) log_S = librosa.core.logamplitude

How to generate file including spectrum of frequencies of wav/riff sound file? I would like to use linux command line. I know the cool sox function to generate png spectrograms sox sound.wav -n spectrogram But I do not need visual representation of the spectrum of frequencies. I just want to get spectrum of frequencies in data file so I can work on them. I believe that there must be an option using sox. Sox need to generate that data before plotting it. How to get this? Not sure, maybe the second solution is exporting wav file into the dat file. Each sample from dat file is a measure of the

The following code generates a spectrogram using either scipy.signal.spectrogram or matplotlib.pyplot.specgram . The color contrast of the specgram function is, however, rather low. Is there a way to increase it? import numpy as np from scipy import signal import matplotlib.pyplot as plt # Generate data fs = 10e3 N = 5e4 amp = 4 * np.sqrt(2) noise_power = 0.01 * fs / 2 time = np.arange(N) / float(fs) mod = 800*np.cos(2*np.pi*0.2*time) carrier = amp * np.sin(2*np.pi*time + mod) noise = np.random.normal(scale=np.sqrt(noise_power), size=time.shape) noise *= np.exp(-time/5) x = carrier + noise

So here's the idea: you can generate a spectrogram from an audio file using shorttime Fourier transform (stft). Then some people have generated something called a "binary mask" to generate different audio (ie. with background noise removed etc.) from the inverse stft. Here's what I understand: stft is a simple equation that is applied to the audio file, which generates the information that can easily be displayed a spectrogram. By taking the inverse of the stft matrix, and multiplying it by a matrix of the same size (the binary matrix) you can create a new matrix with information to generate

The two spectrograms are in the same dimension. I tried S = spectrogram() to get the vector S , but I don't know how to draw back to spectrogram with it. In the documentation , it says that the images are drawn with the command surf(T,F,10*log10(abs(P))); . So for example, you could plot the difference of two of these images with: %# make some data T = 0:0.001:2; X1 = chirp(T,100,1,200,'q'); X2 = chirp(T,150,1,200,'q'); %# plot the first spectrogram subplot(3,1,1); spectrogram(X1,128,120,128,1E3); title('Quadratic chirp 100Hz') %# plot the second spectrogram subplot(3,1,2); spectrogram(X2,128

I have a program in MATLAB which I want to port to Python. The problem is that in it I use the built-in spectrogram function and, although the matplotlib specgram function seems identical, I'm getting different results when I run both. These is the code I've been running. MATLAB: data = 1:999; %Dummy data. Just for testing. Fs = 8000; % All the songs we'll be working on will be sampled at an 8KHz rate tWindow = 64e-3; % The window must be long enough to get 64ms of the signal NWindow = Fs*tWindow; % Number of elements the window must have window = hamming(NWindow); % Window used in the