New answers tagged

0

Good for what purpose? There are always trade-offs. You can play with the color palette or function, or do local non-linear color selection. You can try compositing/stacking multiple resolutions of spectrograms (both time and frequency) for higher contrast and perhaps more interesting appearances, but that process can add its own artifacts.


3

Orthogonality provides an interesting backbone to the structure of the filter-banks (FB). First, from an analysis FB, the synthesis FB is very direct, so it can ease implementations. Second, the orthogonality often allows faster implementations, as there is "little redundancy" in computation. Third, orthogonality ensures that matrices are well-conditioned, ...


0

Having an orthogonal basis makes finding coefficients a lot easier. It makes the matrix that needs to be inverted a diagonal matrix making inversion trivial. With the DFT it is so trivial it is implicit.


1

I would look into the EBU R-128 method of loudness measuring. Based on an ITU algorithm, it is used to determine loudness for TV which consist mostly of dialogue. ITU Docs EBU R-128 Docs


0

This has an implementation of the convolution using overlap-add method in python, maybe this will be useful.


2

This is expected and a consquence of Parseval's theorem. Loosely speaking, it's a flavor of energy conservation: the total energy of the signal doesn't change when you transform it from the time domain into the frequency domain so the energy calculated in either domain must be the same.


0

You can't, at least not strictly. Low pass filters with an all positive impulse response will always have a very wide transition band. However, if you want to do audio envelope detection both Hilbert Transform and low pass filters are the wrong tools for the job: Hilbert Transformers don't work well on broad band signals and low pass filters mess up your ...


0

It looks like you are reading a stereo file, so you have a left and a right channel. You can do a DFT on the left or a DFT of the right or the mono or all of the above. It really depends on your specific application and requirements.


0

You are assuming that a parallel high pass and low pass add up to "flat". In most cases, they do not. You have to carefully design both the phase and the amplitude responses in the transition band to match each other. There are a few classes of filters that are useful here 1st order lowpass/highpass to add up to unity Odd order butterworth filters add up ...


0

I think, the problem lies here: scale back as a result of the FFT clear non overlapping area in innput/output signal mic. Why are you doing this? You are using a Hamming window with 50% overlap, summed up, this yields a constant one. If you delete the "non overlapping" part, you effectively change the window you are using to a weird "half hamming"...


0

First, I would check the positioning of sound level meter and microphone. If you are putting them close to the oscilloscope a few centimeters of displacement may change the measured value dramatically. (6dB/doubling of distance) Second, which microphone do you use? The link you provided leads to a preamplifier. The actual capsule can either be a free field ...


1

It's a Lowpass-Feedback Comb Filter, so let's dissect this one at a time: Comb filter: You have delay line and add the output back to the original signal. That gives you a single echo Feedback: You take some of the output of the delay line and put it back into the input of the delay line. That gives you a series of echo's that repeat regularly. You need to ...


2

If your code is working correctly, than there should be no aliasing. Most likely this is a problem with your playback system. Most sound cards in computers are terrible and will create a lot of noise and other artifacts. Since the 19 kHz tone is inaudible for most people, you just hear the artifacts. It's also possible that you turn up the volume too high....


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what you are describing is equivalent to a man-in-the-middle network attack. https://en.m.wikipedia.org/wiki/Man-in-the-middle_attack . If the original file was watermarked, that would offer the possibility of some authentication. Unless the individual who edited the file was inept, I don’t believe that you can in general detect the difference.


0

That's a really hard problem. If you have access to the original snare stem and the amount of post processing (effects, panning, mastering) is moderate you may be able to pull some of it out with an adaptive filter. There are a few commercial plug ins that do this type of thing, but they all have their strengths and weaknesses so it depends a bit on your ...


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