WikiSQL VS ASH-IR-Dataset

WikiSQL

Natural language processing/understanding/generation is solved (at least in English).

LLMs produce perfectly fluent output and can understand natural language input as well as any human.

However knowledge representation is not solved. We still don't know how to interface a perfect LLM to other systems in the same way a human does things like looking up facts we aren't confident of or using a calculator to do math we cant' do in our head.

These are very significant problems and super important. But they are more adjacent to NLP in the same way tasks like something like Text-to-SQL [1] isn't a pure NLP task.

[1] for example https://github.com/salesforce/WikiSQL

Well, as far as I know Dolby Atmos does the following. It will pass any surround information as "BED" and then process available Atmos specific data, which is normally represented through 7.1.x portion of the setup. DTS is similar in that. So if you have ability to pass Both information, yes they are awesome. If you can only manage "BED," I still think it's well worth it. But if you can only provide Stereo source. No point because all you are going to get is Stereo playback. Now there are many options for up-mixing like using this: https://sourceforge.net/projects/stereo-to-7-1-converter/ and other commercial means. Which then will be worth getting. Another possibility is to use non-commercial headphone virtualization like HeSuvi: https://sourceforge.net/projects/hesuvi/ or better yet follow this project: https://github.com/ShanonPearce/ASH-IR-Dataset, which not only gives you binaural signal to your headphone but also simulates a chosen environment.