Have you heard a difference when bi-amping your speakers?

[AudiocRaver]

The music need not e chosen at random, I see no benefit in that.

Here is a spectrum analysis snapshot of Burn The Witch by Radiohead, a song I might listen to any day of the week. Might as well use a real example. I do not listen to average music, I listen to specific songs.

Full spectrum, a fairly even distribution of energy with no shortage of upper mids and highs. The rms signal levels are -11 dBFS left and -8.3 dBFS right.

Span2

• AudiocRaver
• Mar 27, 2018

Same passage, but with a 12 dB/oct high-pass filter at 500 Hz. The rms signal levels have only dropped to -13.6 dBFS and -11.8 dBFS, a difference of 2.6 and 3.5 dB respectively, indicating that MF and HF energy accounts for about half of the energy of the track at that point in time.

Span1

• AudiocRaver
• Mar 27, 2018

 

[AudiocRaver]

We should not hijack this thread any farther. If you would like to continue this discussion, start a new thread and I will link to it from here.

 

[dc2bluelight]

The music need not e chosen at random, I see no benefit in that.

Random selection is key to understanding the general trend. Otherwise you have essentially a single data point (the spectrum of one of your favorite songs), which doesn't represent anything but the spectrum for that song. That's not an answer to design with.

Here is a spectrum analysis snapshot of Burn The Witch by Radiohead, a song I might listen to any day of the week. Might as well use a real example. I do not listen to average music, I listen to specific songs.

I though the tread might be addressing the needs of other people, perhaps provide generally applicable knowlege, but...well... ok...

Full spectrum, a fairly even distribution of energy with no shortage of upper mids and highs. The rms signal levels are -11 dBFS left and -8.3 dBFS right.

That's not what your graph shows.

Same passage, but with a 12 dB/oct high-pass filter at 500 Hz. The rms signal levels have only dropped to -13.6 dBFS and -11.8 dBFS, a difference of 2.6 and 3.5 dB respectively, indicating that MF and HF energy accounts for about half of the energy of the track at that point in time.

Still not what your graph shows.

This is EXACTLY the problem! Here's my analysis, same piece:

Before we jump down this rabbit hole, consider that if your graph were an actual representation of reality, no tweeters would survive! Ever! Your graph shows equal energy across the spectrum. We know that cannot be true, if for no other reason than tweeters typically have maximum power handling figures that are a small fraction of woofers. But keep going...

The difference is you're using a audio Real Time Analyzer, I'm using a spectrum analyzer. Both fundamentally use an FFT, but the difference is in how the data is presented. A spectrum analyzer breaks the spectrum up into fixed bandwidth "bins", the RTA breaks it up into octave-bandwidth (or fractional-octave) bins, which increase in absolute bandwidth as frequency goes up, thereby including progressively more energy in each band. Both techniques have their purposes. But for determining spectral energy distribution you cannot us an analyzer with varying bandwidth, or you'll get the wrong answer, which you did.

We should not hijack this thread any farther. If you would like to continue this discussion, start a new thread and I will link to it from here.

Fine. Whatever. I don't really see the point though. It's hardly a hijack. Understanding energy distribution is key to understanding why things like passive bi-amping usually offer zero benefit. The topics are logically linked. If you separate them, I don't see the point in continuing, as a key association will be lost.