Comments (8)
Hi, this is a pretty broad question. The quality of the separation will depend a lot on what you want to do and the constraints you are working with. For example, if the microphones are placed closely together, the separation performance will not be so good in the low frequency part.
One way to separate is to create beamformers towards the sources. Beamformers work by combining the microphone signals in a way that creates constructive interferences towards the sources. Now there are, as you might have noticed, many ways to do that.
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Yes thats true, I experienced this as I am working with PS3EYE. Right now I am using webrtc beamforming module. I wanted to know how to use the beamformer module present in this pyroroomacoustics.
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Hi,
I want to use beamforming code present in this repo, could you give me a glimpse of how to use it. I have matrix creator a circular array with 8 mics. I want to beamform and do source separation
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Hi any help possible
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Hi @pathasreedhar , there are two beamforming examples in the examples
folder. Did you take a look there ?
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yes.. I have seen them, these examples use simulations, I am unable to use them for real time readings, like for example in time domain, you used some beam forming filters suitable for simulated readings.
I want to know how we select these parameters
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You can use the Beamformer
object on recorded signal as well.
'''
This example shows how to create delay and sum beamformers
'''
from __future__ import print_function, division
import numpy as np
import matplotlib.pyplot as plt
from scipy.io import wavfile
import pyroomacoustics as pra
# Open your recorded signals
fs, my_recording = wavfile.read('my_recording.wav')
# Create a room around your array
# this is merely a convenience, it doesn't have to be the real room
room = pra.ShoeBox([4,6], fs=fs)
# Add a source somewhere in the room
# You don't need to know the exact location, just set
room.add_source(<coordinate of the source relative to your microphone array>)
# Create a linear array beamformer with 4 microphones
# with angle 0 degrees and inter mic distance 10 cm
R = <coordinates of the microphones on your array>
room.add_microphone_array(pra.Beamformer(R, room.fs))
# Add the recorded signals in your array
room.mic_array.signals = my_recording
# Now compute the delay and sum weights for the beamformer
# Use the far field option if you don't know the exact distance
# from source to microphone array
room.mic_array.rake_delay_and_sum_weights(room.sources[0][:1], far_field=True)
# alternatively you can compute your own weights and set them directly
# room.mic_array.weights = my_weights
# Now compute the output of the beamformer
output = room.mic_array.process()
I agree that the interface for the beamforming is not ideal at the moment. Hopefully, I can improve this in the future.
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Closing this due to lack of activity.
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Related Issues (20)
- Adding a diffuser
- problem in pip HOT 4
- Has Gaussian-Laplace IVA (IVA-GL) been also implemented in this library? HOT 1
- Bug in auxiva? Script did not show any error, but got nan in the result of source matrix HOT 2
- Compute RIR up to a K (earliest or strongest) reflection (or max time)
- ValueError: operands could not be broadcast together with shapes (2709,96) (2500,1) (2709,96)
- Waves in the signal after convolving the signal with the RIR HOT 3
- Question regarding materials HOT 1
- scipy.signal.hann is deprecated in SciPy 1.13.0
- How to simulation energy decrease? HOT 8
- why conj in ILRMA HOT 4
- Error in pyroomacoustics/pyroomacoustics /beamforming.py HOT 1
- Differences With Other Libraries HOT 1
- Help me understand energy scaling HOT 4
- libroom.rir_builder error: "The rir array is too small for the maximum time recorded" HOT 13
- Plot of Microphones HOT 1
- directivity argument of Room.add_microphone_array HOT 1
- About directional source signal
- Potential bug when generating RT60 using v0.7.5 HOT 6
- CMU-ARCTIC’s accent tags are different from those shown on the official website
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