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I want to try and setup a dual microphone system that does some sort of subtraction in order to enhance speech quality. The aim is to implement a communication system on a wearable sportsvest - all school related. I am working with two omnidirectional mems-microphones, one attached to the chest area, and one attached to the back of the body. My thought process was that i could use the backmounted mic, to capture and remove any background noise from the final audio output, by subtracting it's audiooutput from the speech-microphone coming from the chestmounted mic. I've read a bunch of articles online about this principle being applied in Smartphone devices when used in hands-free mode.
I have tried the build-in beamforming algorithm as well as simple time-domain subtraction but none of these seem to be working very well.
It is inspired by classic electronic musical instruments of the past, including spectral processors, additive synthesis, vocoders, and resonators especially the Buchla 296 and Touché, but it takes a physical form more resembling the classic analog dual complex oscillator in the lineage of the Buchla 259 and the Make Noise DPO.
The Shure Axient Digital ADX5D dual-channel wireless receiver delivers superior RF performance, spectral efficiency, and transparent audio quality in a portable, slot-in form. As an Axient Digital ADX Series wireless receiver,the ADX5D features ShowLink Direct Mode that allows remote control of Axient Digital transmitters without the need of external equipment.*The sound and performance that touring audio professionals have adopted as industry standard is now available to audio professionals in film and broadcast. Robust RF. Impeccable audio. Axient Digital quality and performance. All in a portable, slot-in design. Premium portable wireless.
Dual Energy spectral imaging supports you in making confident diagnostic and treatment decisions based on answers only available with Dual Energy. This helps you to impact clinical outcomes and deliver optimal care for your patients.
At the same time, you benefit from the automatic selection and the right combination of the scan settings. Multiple kV levels let you adapt to the patient's size,with a large spectral separation means even the most demanding exams, like visualizing bone marrow edemas, are possible. The dose level of a Dual Source CT scanner is comparable to a single-source acquisition, but the built-in tin filter enables even lower doses than a conventional 120 kV CT scan.
TwinBeam Dual Energy (TBDE) CT allows simultaneous acquisition of high and low kV datasets in a single spectral CT scan by splitting the X-ray beam with two filters, one made of gold and the second made of tin, before it reaches the patient, enabling high-contrast dynamic applications.
CARE kV, a fully automated feature that tailors the tube voltage to the individual patient and clinical task, complements existing dose reduction technologies for dose-neutral Dual Energy acquisitions without compromising image quality.
Image quality is crucial for reliable DECT imaging since dual energy data processing is sensitive to small changes of the Hounsfield units. Relevant criteria comprise the spectral separation and temporal coherence of the low and high energy data, as well as the temporal and spatial resolution of the CT images, but of course also the dose efficiency or the workflow aspects play an important role in enabling efficient DECT imaging in daily routine.
The single energy gray-scale image (indicated on the left) does not allow for the differentiation of the two materials. Spectral imaging with inferior spectral separation (middle image) allows material differentiation but with limited differentiation (resulting in noise in the green/orange material space). As indicated by the right image, using Dual Source Dual Energy CT or TwinSpiral Dual Energy results in excellent spectral separation with clear differentiation.
Dual Energy spectral imaging can provide additional diagnostic information, but this should not come at the expense of an increased patient dose compared to a conventional single energy examination. Siemens Healthineers Dual Energy CT solutions incorporate all state-of-the-art dose reduction features like tube current modulation or iterative reconstruction to allow dose-neutral spectral imaging acquisitions.
By fusing low- and high-kV data into the DICOM conformant spectral imaging data format, Spectral Post-Processing (SPP), data and transfer times to PACS are reduced. In your PACS, the SPP dataset shows a single DICOM dataset either as Mixed or Monoenergetic Plus images while keeping the low and high Dual Energy information intact. SPP also enables Interactive Spectral Imaging and gives the user retrospective access to the encapsulated spectral data at any time.
myExam Companion smoothly navigates users through spectral imaging CT examinations by sharing built-in expertise, characterizing real-time patient input, and adjusting key parameters to each patient. It also guides you to Dual Energy reconstructions, such as Iodine Maps or Virtual Non-Contrast, which are PACS-ready. This is valuable for radiologists, giving them additional information to work with.
Krauss B, Grand KL, Schmidt BT, Flohr TG. The importance of spectral separation : an assessment of dual energy spectral seperation for quantitative ability and dose efficiency. Invest Radiol. 2015;50(2):114-118.
I am currently reading 1024 bytes of a 16 bit dual channel 44,100 Hz sample rate audio stream and averaging the amplitude of the 2 channels together. So now I have an array of 256 signed shorts. I now want to preform a fft on that array, using a module like numpy, and use the result to create the graphical spectrum analyzer, which, to start will just be 32 bars.
The array you are showing is the Fourier Transform coefficients of the audio signal. These coefficients can be used to get the frequency content of the audio. The FFT is defined for complex valued input functions, so the coefficients you get out will be imaginary numbers even though your input is all real values. In order to get the amount of power in each frequency, you need to calculate the magnitude of the FFT coefficient for each frequency. This is not just the real component of the coefficient, you need to calculate the square root of the sum of the square of its real and imaginary components. That is, if your coefficient is a + b*j, then its magnitude is sqrt(a^2 + b^2).
Once you have calculated the magnitude of each FFT coefficient, you need to figure out which audio frequency each FFT coefficient belongs to. An N point FFT will give you the frequency content of your signal at N equally spaced frequencies, starting at 0. Because your sampling frequency is 44100 samples / sec. and the number of points in your FFT is 256, your frequency spacing is 44100 / 256 = 172 Hz (approximately)
So that is what those numbers represent. Converting to a percentage of height could be done by scaling each frequency component magnitude by the sum of all component magnitudes. Although, that would only give you a representation of the relative frequency distribution, and not the actual power for each frequency. You could try scaling by the maximum magnitude possible for a frequency component, but I'm not sure that that would display very well. The quickest way to find a workable scaling factor would be to experiment on loud and soft audio signals to find the right setting.
Finally, you should be averaging the two channels together if you want to show the frequency content of the entire audio signal as a whole. You are mixing the stereo audio into mono audio and showing the combined frequencies. If you want two separate displays for right and left frequencies, then you will need to perform the Fourier Transform on each channel separately.
I designed and made a whole 10 led bar spectrum analyzer by Python. Instead to use the nunmpy library (too big and useless to get just the FFT) a python pyd module (just 27KB) to get the FFT and to split the entire audio spectrum to bands was created.
The Make Noise/soundhack Spectraphon music synthesizer module is a dual Spectral Oscillator coded by Tom Erbe of soundhack. It uses real-time spectral analysis and resynthesis to create new sounds from those that already exist. It is inspired by classic electronic musical instruments of the past, including spectral processors, additive synthesis, vocoders, and resonators especially the Buchla 296 and Touché, but it takes a physical form more resembling the classic analog dual complex oscillator in the lineage of the Buchla 259 and the Make Noise DPO.
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