Acen
There are more frequencies in the high-range, so it naturally sounds considerably higher pitched.
i.e. a C6 on a keyboard sits at around 1Khz (1046.502 to be exact) and a C#6 is 1108.731 KHz (a difference of 62.229 Hz)
While a C3 is 130.8128, and C#3 is 138.5913 (a difference of only 7.7785 Hz).
Then using an entire octave as an example, C3 (130.8128) to C4 (261.6256) = 130.8128 (0Hz up to C3)
vs C6 (1046.502) to C7 (2093.005) = 1046.503 (0hz up to c6 +- 0.001hz)
The orders of magnitude in power/loudness is pretty astonishing.
When introducing decibels to new audio engineers, we generally introduce it as a 3db increase is a doubling in power, a 10db increase is a 10x increase in power.
It gets silly when you start talking sound pressure level, because how people perceive a 10x increase in the output power, is about a doubling of the perceived loudness.
[1] Author link (includes link to source): https://www.intelliscapesolutions.com/apps/caffeine
[2] Original author link (stopped updating before OSX Mojave): https://www.lightheadsw.com/caffeine/
I've been using Flux studio session analyser to visualise audio signals for mixing In-ear monitors for live audio[1] from my Cue mix.
Might write a quick dodgy thing to add this to my analysis stack. Could be cool.
https://www.cloudflare.com/products/turnstile/
Don't get any goofy puzzles which is nice.
The other, is that people might be using Github to share stuff they've come up with other developers, but having an AI parse that information means that there's a disconnect between giver and receiver. It removes a chunk of the feedback loop being possible, which makes it so rather than it being a community of developers, it becomes something more akin to content creators and lurkers. That's not necessarily a bad thing, due to it opening up the sheer number of possible usages that end up using something. But it would minimize community feedback.
An alternative for a local network is running NDI. That's how for events we stream a bunch of remote cameras (and even computers on the network) into visual displays.
There are NDI apps for most phones etc.
Standing somewhere in the audience space and listening for & looking at each person on stage individually to ensure they're part of the mix.
Maybe I should implement something physical. Though pointing at the band would usually make them stop and ask what I'm needing
Say I have a mic on a stand at the back of a room (i.e. Earthworks M30), someone can enter the door from the opposite side, and quietly walk somewhere else in the room. The mic will pick up each step they're making in a pretty obvious fashion on a spectrograph in Smaart. Or a fan from an LED light hanging from truss in the ceiling.
Edit: That might be from one of the plugins they're using on their WIX CMS though.
It's pretty painful to use when you want to do something simple in code like explode an array, take a few of the values from that and implode back into an array again.
Things like AWS Quicksight or Google Data Studio might be in the same sort of world too.
We're building some new infrastructure for a service that is also new, using terraform. Which only our devops have used before.
It's an interesting time.
AWS Cognito with app clients and not user pools + AWS API gateway, connecting to a system linked with dynamodb, Kinesis data stream and firehose.
Like each part stand alone is documented okay with specific circumstances. But nothing interlinking at anything past the basic level.
Trial and error is brutal.
Usually a person won't notice an increase in volume unless it has a 3-5dB (3dB = double in power) increase. And won't perceive a double in volume without a 10dB (10dB = 10x increase in power) increase and even then it depends on the specific frequency.
Some things to check out would be: https://en.wikipedia.org/wiki/Stevens%27s_power_law https://en.wikipedia.org/wiki/Weber%E2%80%93Fechner_law (and thus Just Noticable Difference [https://en.wikipedia.org/wiki/Just-noticeable_difference])