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2025Working prototype

Compensation Filter for Live Venues

Can the acoustic character of another venue be reproduced in the current space?

Preparing submission

SA4ME: International Workshop on Spatial Audio for Multisensory Experiences · IEEE VR 2027 ↗
I am preparing a paper for submission to the IEEE VR 2027 SA4ME workshop, analysing how the effectiveness of spatial audio compensation varies across listening positions and how those differences relate to acoustic measures.

Evidence at a glanceMeasured result and next comparison
UncorrectedProposed method

Error (dB) · lower is closer to the target response

SLF
2.27 → 1.47 dB
SRF
2.67 → 2.35 dB
SLC
3.30 → 2.93 dB
SRC
3.17 → 2.17 dB
SLB
2.40 → 2.32 dB
SRB
2.33 → 2.22 dB
Mean spectral error against the target hall at fourth-row center, 0–40 ms and 125 Hz–4 kHz: 2.69 → 2.24 dB. First-stage comparison on data used to derive the filters. Other seats and direct target-IR convolution are planned measurements. Paper, Table 3 ↗

My contribution

Wonder
Can the acoustic character of another venue be reproduced in the current space?
Build
Analysed and aligned six speaker-path IRs in Python, designed regularized inverse FIR filters, and implemented real-time multichannel convolution in Max/MSP. Convology XT adds the target hall’s late reverberation separately.
External tools & AI

I used Python for IR alignment and filter generation, and Max/MSP and Convology XT for playback. AI helped me write the Python code.

Find out
At fourth-row center, mean spectral error fell from 2.69 to 2.24 dB on the measurements used to design the filters. Improvement at other seats and a perceptual match to the target hall remain unverified.

Next step

Measure other seats with new data, compare uncorrected sound, direct target-IR convolution, and this method, then run listening tests.

Process & photos

Playing a target hall’s impulse response (IR) in another venue also adds the current venue’s response. I wanted to correct the current room’s coloration before adding the target hall’s reverberation.

I measured six surround-loudspeaker-to-microphone paths and used Python to align them with the target IR. For each channel I designed a Tikhonov-regularized inverse filter, G = A·B* / (|B|² + λ), where A is the target hall IR and B is the current venue’s path. The regularization limits gain where the venue’s response is weak. I aligned the IRs with GCC-PHAT and fractional-delay correction, applied correction only in the 125 Hz–4 kHz band, smoothed the response, and capped the gain. The final filter is a 226 ms FIR.

Max/MSP applies a separate compensation filter to each of the six surround speakers in real time. Convology XT adds the target hall’s reverberation from about 200 ms onward. The main PA carries the direct sound.

At the fourth-row center, mean spectral error fell from 2.69 to 2.24 dB across six channels. This comparison uses the same path measurements that were used to create the filters. It does not establish improvement at other seats or a perceptual match to the target hall.