- Measure or obtain the frequency response data for both the source microphone and the target microphone.
- Use the frequency response data to analyze the differences between the source and target microphones. This can involve calculating the magnitude and phase differences at different frequencies and angles.
- Based on the differences identified in step 2, design a compensation filter that can modify the frequency response of the target microphone to match the source microphone.
- Apply the compensation filter to the audio signals captured by the target microphone.
Create dynamic Beamforming Weights, which depend on the frequency
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Hello,
Iam trying to emulate a specific microphone with the characteristics of another omnidirectional microphone. Which means that i have to somehow adapt the frequencyresponse for every single angle for the target microphone.
I can fit the polarpatterns for a single frequency, with deriving the beam weights for that special Frequency. But with changing frequencys the polarpattern of the target microphone changes. That means that i have to find a way to adapt the beamweights depending on the frequency, right?
Is there any function or toolbox which can help me with that?
Thanks,
Chris
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Anshuman
am 30 Aug. 2023
Hi Christoph,
In MATLAB, you can use the Signal Processing Toolbox to help you with this task. The toolbox provides various functions for working with audio signals and performing signal processing operations. Here's a general approach you can follow:
The Signal Processing Toolbox in MATLAB provides functions for designing and applying filters, such as 'designfilt' for designing FIR or IIR filters, and 'filter' for applying filters to audio signals. You can also use functions like 'freqz' to visualize the frequency response of filters.
Hope it helps
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