This is not a way to make your room magically sound good, but if you're fighting with a bunch of standing waves and are not able to properly cut them by ear, this will be useful.
Even if I was waiting for a Sonarworks Xref20R4 to arrive, i was too impatient, and yesterday an idea came to my mind.
What if I find the sweet spot of the room?
Can I derive the right equalization by the difference between it and the real listening point, given that all the other variables (room,speakers,mic itself) remain the same?
Of course you need at least a mic that is able to capture the frequencies to be corrected with a good SNR, this was indeed my case.
So, what i did was:
play and record a sine sweep in the sweet spot -> sweet_sine.wav
play and record a sine sweep in the bad spot -> bad_sine.wav
Imported the wavs in audacity and normalized them to 0.0dB
At this point maybe rew could do the work by itself by subtracting responses an equalizing the resulting one, but i wasn't able to do that, but one thing crossed my mind, the software i was looking for was AutoEq
Even if it was meant to correct headphones/earbuds, it has a nice feature that given two measurements, is able to make an headphone sound like another.
I've exploited that function to make my bad spot to sound like my sweet spot.
So, I imported the wavs in RoomEqWizard and exported the measurement as text csv, comma separated fields, frequancyt step: 0.09, no smoothing at all:
sweet_sine.wav -> /koko/sweeps/sweet_sine.csv
bad_sine.wav ->/koko/sweeps/bad_sine/bad_sine.csv
AutoEq is surprisingly able to read the csv exported by rev with no modifications, given that you export as comma as field separator.
Given that compensation/zero.csv is a file provided by AutoEq when youi don't need to compensate anything, in the end the command given was:
Which produced the following:
I admit, i've had to strip equalizations at higher frequencies, because they were simply wrong, probably because the SNR of the microphone wasn't good enough and i couldn't push the volume higher at the time i made the measurement (also, i discovered an error in the measurement of bad_sine.wav, probably the microphone moved during the sweep!)
I've also corrected the "power" of the equalization by dividing all the cuts by a factor of two; it was just to extreme, can't say why.
But at least i was able to identify the center frequencies of the standing waves and their widths, which was exactly what i need.
Hoping this could be helpful for someone else, it took me the entire day
Even if I was waiting for a Sonarworks Xref20R4 to arrive, i was too impatient, and yesterday an idea came to my mind.
What if I find the sweet spot of the room?
Can I derive the right equalization by the difference between it and the real listening point, given that all the other variables (room,speakers,mic itself) remain the same?
Of course you need at least a mic that is able to capture the frequencies to be corrected with a good SNR, this was indeed my case.
So, what i did was:
play and record a sine sweep in the sweet spot -> sweet_sine.wav
play and record a sine sweep in the bad spot -> bad_sine.wav
Imported the wavs in audacity and normalized them to 0.0dB
At this point maybe rew could do the work by itself by subtracting responses an equalizing the resulting one, but i wasn't able to do that, but one thing crossed my mind, the software i was looking for was AutoEq
Even if it was meant to correct headphones/earbuds, it has a nice feature that given two measurements, is able to make an headphone sound like another.
I've exploited that function to make my bad spot to sound like my sweet spot.
So, I imported the wavs in RoomEqWizard and exported the measurement as text csv, comma separated fields, frequancyt step: 0.09, no smoothing at all:
sweet_sine.wav -> /koko/sweeps/sweet_sine.csv
bad_sine.wav ->/koko/sweeps/bad_sine/bad_sine.csv
AutoEq is surprisingly able to read the csv exported by rev with no modifications, given that you export as comma as field separator.
Given that compensation/zero.csv is a file provided by AutoEq when youi don't need to compensate anything, in the end the command given was:
Code:
python ./autoeq.py --input_dir /koko/sweeps/bad_sine/bad_sine.csv --output_dir /koko/sweeps/MyResults --sound_signature /koko/sweeps/sweet_sine.csv --show_plot --equalize --compensation compensation/zero.csv --parametric_eq
Code:
Preamp: -6.5 dB
Filter 1: ON PK Fc 16 Hz Gain 7.1 dB Q 0.85
Filter 2: ON PK Fc 68 Hz Gain -20.4 dB Q 1.61
Filter 3: ON PK Fc 155 Hz Gain -12.9 dB Q 2.04
Filter 4: ON PK Fc 280 Hz Gain -12.4 dB Q 4.96
Filter 5: ON PK Fc 625 Hz Gain -15.2 dB Q 0.96
Filter 6: ON PK Fc 664 Hz Gain 11.4 dB Q 6.58
Filter 7: ON PK Fc 1592 Hz Gain -11.9 dB Q 2.77
Filter 8: ON PK Fc 1874 Hz Gain 3.8 dB Q 3.62
Filter 9: ON PK Fc 2241 Hz Gain -10.5 dB Q 2.22
Filter 10: ON PK Fc 2347 Hz Gain 6.5 dB Q 1.38
Filter 11: ON PK Fc 3645 Hz Gain 4.1 dB Q 4.53
Filter 12: ON PK Fc 4588 Hz Gain -12.9 dB Q 2.60
Filter 13: ON PK Fc 5154 Hz Gain 7.3 dB Q 2.85
Filter 14: ON PK Fc 5647 Hz Gain 6.8 dB Q 1.39
Filter 15: ON PK Fc 5816 Hz Gain -4.3 dB Q 2.15
Filter 16: ON PK Fc 16565 Hz Gain -0.2 dB Q 2.15
Filter 17: ON PK Fc 17596 Hz Gain 6.1 dB Q 0.11
I admit, i've had to strip equalizations at higher frequencies, because they were simply wrong, probably because the SNR of the microphone wasn't good enough and i couldn't push the volume higher at the time i made the measurement (also, i discovered an error in the measurement of bad_sine.wav, probably the microphone moved during the sweep!)
I've also corrected the "power" of the equalization by dividing all the cuts by a factor of two; it was just to extreme, can't say why.
But at least i was able to identify the center frequencies of the standing waves and their widths, which was exactly what i need.
Hoping this could be helpful for someone else, it took me the entire day
Last edited: