jojek
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Convolution : Anechoic Speech signal and Impulse response
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3 votes

I have no access to your audio files so I've downloaded: IR from here (mono/r1_omni.wav) - it's a really long one Anechoic recording from here (operatic-voice/mono/singing.wav) Resampled voice ...

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Audio classification without deep learning
3 votes

From what you've mentioned it looks like the task is for environmental sound event detection. I think that the best starting point for you is to check the DCASE challenge (Detection and Classification ...

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How do I get the volume levels from an audio file?
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3 votes

I can give you a quick and hacky solution with sox that can be easily installed on any Linux distribution. sox in.wav -n trim 0 0.1 stats : newfile : restart 2>&1 | grep 'RMS lev dB' | awk '{ ...

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How can an audio segment report an integrated loudness (LUFS) greater than 0
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1 votes

I did download this annoying video and analyzed the part with a vuvuzela. You should take a note that: This part is clipped The audio is stereo And that pretty much solves the mystery. If you ...

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periodicity coefficient
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4 votes

I suggest using Spectral Flatness, aka Wiener Entropy. It is defined as a ratio of geometric and arithmetic mean of the magnitude spectra $X(k)$: $$\Xi=\dfrac{\sqrt[K]{\prod_{k=0}^{K} X(k)}}{\frac{1}{...

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FFT filter to remove cd scratch
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3 votes

This approach with notch filter with not work. All clicks are impulse-like sounds and we know that an impulse has frequency content at almost every frequency. What you are trying to do, by applying ...

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Working with a sound's magnitude instead of amplitude
0 votes

I am not sure what do you mean by magnitude, but you should be getting a waveform that's perfectly fine for further analysis you wish to do. Just keep in mind that you don't know the frequency ...

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Calculation of Reverberation Time (RT60) from the Impulse Response
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19 votes

Encouraged by Hilmar, I've decided to update the answer with all the steps necessary to calculate the Reverberation Time from a scratch. Presumably, it will be useful for others interested in this ...

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SPL values from FFT of microphone signal
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1 votes

Let's assume that signal you are analysing is sinusoid with amplitude $A$: $x=a\sin{2\pi f_{0} t}$ Its RMS value of amplitude is then: $\dfrac{a}{\sqrt{2}}$ as you noticed in your code. Before ...

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filterbank: understand the different responses at the center frequency of each filter
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2 votes

Normalizing the filterbanks by their widths is optional and totally up to you (similarly to the warping scale Mel/Bark). Depending on your application, you can start without normalization and see what ...

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How to normalize frequency response charts
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2 votes

First of all, I wouldn't worry too much about the speaker response since it is relatively flat and the microphone has a much bigger roll-off. Since you've captured the frequency response using sweep,...

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Is this a correct interpretation of the DCT step in MFCC calculation?
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18 votes

Let me start from the beginning. The standard way of calculating cepstrum is following: $$C(x(t))=\mathcal{F}^{-1}[\log(\mathcal{F}[x(t)])] $$ In the case of the MFCC coefficients case is a bit ...

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FFT on a random signal
2 votes

First of all you should take the magnitude of the FFT (use abs function) - what you've plotted is just a real part of FFT. Secondly, depending on what you want to achieve, I would suggest to detrend ...

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Two voice pronunciation comparison similarity MFCC + DTW
4 votes

I will answer your questions in reverse order. 4: DTW (Dynamic Time Warping) is not a library but an algorithm. It allows aligning two sequences by warping them in time. You can use it for pretty ...

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Converting mel spectrogram to spectrogram
3 votes

Nowadays the easiest thing would be to use librosa for this task. It has the mel_to_stft function which does exactly what you want. As others have mentioned, this reconstruction is lossy and only ...

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Meaning of Hilbert Transform
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44 votes

One application of the Hilbert Transform is to obtain a so-called Analytic Signal. For signal $s(t)$, its Hilbert Transform $\hat{s}(t)$ is defined as a composition: $$s_A(t)=s(t)+j\hat{s}(t) $$ The ...

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Feature extraction/reduction using DWT
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10 votes

I think it is kind'a similar to soft and hard thresholding using in wavelet de-noising. Have you come across this topic? pywt has already an in-built function for this purpose. Please take a closer ...

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Why do I have frequency leakage in DFT after zero padding if frequency resolution is fine?
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18 votes

This phenomenon has nothing to do with spectral leakage. What you are observing is the effect of zero padding. Given a number of samples $N$, there is a maximum possible frequency resolution $\Delta f$...

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What's the correct graphical interpretation of a series of MFCC vectors?
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11 votes

The way MFCC's are always used is by feeding them into the classifier. This can be done on a frame-by-frame basis (12x1 vector), or by concatenating (12xN) - same as a spectrogram. Thus for DTW, you ...

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How do I manually plot the frequency response of a bandpass Butterworth filter in MATLAB without freqz function?
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28 votes

We know that in general transfer function of a filter is given by: $$H(z)=\dfrac{\sum_{k=0}^{M}b_kz^{-k}}{\sum_{k=0}^{N}a_kz^{-k}} $$ Now substitute $z=e^{j\omega}$ to evaluate the transfer function ...

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Baby Cry recognition robust against the distance
1 votes

This question is very broad and it is not possible to give a very good answer without even knowing the internals of your system (the type of the network and features make a big difference). However, I ...

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MFCC window size at different sampling rates
1 votes

I will answer your question from my experience. For most of the time, I've been using window length which is a power of 2, trying a few overlap percentages, training the system and picking the one ...

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Explanation of OASPL and SEL
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1 votes

Yes, you can calculate it by summing all of the 3rd-octave band pressures. Keep in mind, that if the units are pressure then simple sum and conversion to the decibel scale is enough. However, if you ...

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DSP Concepts Visually Explained
6 votes

Personally, I very much like the interactive visualisations of filters that connect various bits together. There is a great website called MicroModeller DSP (I am not affiliated with it). You can ...

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Is it accurate to say in digital audio that, when a fader is down, then its value is "-$\infty$"?
9 votes

If by "its" you mean the value of the fader, then yes - it's absolutely correct. Fader defines the attenuation of the signal with respect to the reference level. The units are in logarithmic scale. ...

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Apply Low pass Butterworth filter in Python
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10 votes

You should not be using the analog filter - use a digital filter instead. You want the filter to be defined in Z-domain, not S-domain. Also, you should define the time vector with known sampling ...

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Create a third octave spectrum from a time signal
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1 votes

Hate to answer this question, but it is a plotting issue, not the actual design problem. Basically, you don't have enough points at low frequencies cause they are spaced linearly and you are plotting ...

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The Technology Behind Animoji by Apple
3 votes

It's more like a soft answer (I am happy to update it later), but Alex Acero explained the technology behind aniomoji on this years ICASSP 2018. Here is the link. Basically, they are using so-called ...

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STFT amplitude normalization, librosa library
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5 votes

I did answer a similar question a few years back, but can't find it. Basically, you are losing the energy because of the windowing. It's true to say that you should multiply the spectra by 2 in order ...

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How to implement a filter associated to a specific wavelet
3 votes

You've mentioned Butterworth filters for doing the wavelet analysis using bior6.8. If you want to perform the Discrete Wavelet Transform using some specific wavelet, then you must use its Perfect ...

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