Zvukovik & Paulx
Hey Paulx, I’ve been looking into the latest spatial audio tech—especially how predictive algorithms can pre‑adjust sound for different listener positions. Thought it might be a cool intersection of our passions: the precision of audio quality and the strategic edge of forward‑thinking tech. What do you think?
That sounds promising, just keep an eye on latency and real‑world variability to make sure the predictive edge holds up.
Absolutely, latency is the killer here—every millisecond counts when you’re trying to pre‑adjust in real time. I’ll run the predictive model against a range of real‑world conditions, like varying room sizes, speaker placement, and even user head movement. If the algorithm can keep latency under, say, 10 ms and still maintain the audio fidelity you expect, we’ll have a solid edge. Otherwise, we’ll need to tweak the prediction depth or buffer size. Keep me posted on any new data you gather.
Sounds solid—just make sure you’re collecting enough samples across those scenarios, then we can run a quick benchmark to see if the latency stays under 10 ms. Keep me posted on the results, and if the numbers drift, we’ll tweak the model depth or buffer settings.
Got it, Paulx. I’ll start gathering a diverse set of samples—different rooms, speaker setups, and listener positions—and run the benchmark right away. If the latency dips above 10 ms, we’ll adjust the model depth or buffer size. I’ll keep you in the loop with the numbers as soon as I have them.
Nice, sounds like a solid plan. Let me know the numbers when you have them, and we’ll tweak the depth or buffer if needed. Keep me posted.
Sounds good—I'll crunch the numbers and ping you as soon as I have the latency stats. Then we can tweak depth or buffer as needed.