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Author Topic: Frequency analysis  (Read 2968 times)

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Offline Andrea82

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Frequency analysis
« on: April 05, 2015, 01:55:35 PM »
This is a .wav from original master file. It's a Roger Waters The Wall Live show.
I recorded the file in wave at 24 bit 96 khz. The files size is the same as for every show I recorded.
The strange fact is the frequency analysis, that leave doubts about lossless/lossy.
When I convert the wave in flac, I noticed a more small file size and a low bitrate than usual.
The file were recorded by Church Audio cardioids CA11 into a pream STC-9000 and then on a Edirol R09HR.
I would to know the opinion of some experts here about this thing.
Thank you to all
« Last Edit: April 05, 2015, 01:58:29 PM by Andrea82 »

Offline DSatz

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Re: Frequency analysis
« Reply #1 on: April 05, 2015, 03:41:21 PM »
The curve that you show is quite plausible if you were recording a performance that was being played through an amplified (P.A.) system. There isn't generally much sound energy above about 10-12 kHz except for noise and distortion. If you were recording unamplified, acoustic music at very close range, the situation could be rather different.

Either way, it would be easier to see useful information if you chose a logarithmic frequency scale instead of the linear one, and if you set the upper limit of the graph to (say) 25 kHz.

But this type of graph can't tell you anything about lossy vs. lossless compression as such. Why would you imagine that it could do so?

--best regards
music > microphones > a recorder of some sort

Offline Andrea82

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Re: Frequency analysis
« Reply #2 on: April 05, 2015, 04:16:04 PM »
Thanks for reply.
Attached is the logarithmic frequency scale.
I ask here because other shows I taped have the freq over 20000hz.

Offline DSatz

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Re: Frequency analysis
« Reply #3 on: April 05, 2015, 07:31:41 PM »
OK, I think I may understand your concern. "Lossy" compression requires low-pass filtering of some kind; the designers of a codec choose a high-frequency limit that seems appropriate to them. In general it makes sense to filter at 20 kHz (or perhaps a little bit higher if you want to look better on a spec sheet), since any signal energy at higher frequencies will contribute nothing whatsoever that is audible to humans. If the frequency limit is set higher than necessary, the additional signal energy simply wastes space in the channel.

Now, poorly implemented low-pass filters can produce audible side effects, so it's important to use good ones, even though they involve more processing and increased signal latency. The absence of (inaudible) frequencies above 20 kHz does not, in itself, indicate a problem, however. Ultimately, whether a given codec sounds good or bad can only be answered by careful listening.

I believe you when you say that you sometimes get something above 20 kHz in your recordings. But if you are doing the usual kind of distant or semi-distant recording through an amplified system in a public venue, whatever you pick up above about 10 to 12 kHz is mostly noise and distortion. Typically we preserve that garbage because it was part of the actual event and trying to remove it could cause more problems than would be solved. Most people don't perceive the high-frequency garbage as a problem anyway; they're used to hearing it (or to not hearing it, if they've lost those frequencies already, as is quite common).

But significant signal energy above the human audible range is a rather different matter. In no case can humans hear it, but a lot of audio equipment isn't designed to handle it, so audible distortion can be caused by its presence. Unfortunately this distortion causes some people to conclude, incorrectly, that they're hearing signals which actually are completely inaudible to them. (Even some studies published in the AES Journal have suffered from this error: When test subjects hear a difference between playbacks that include energy above 20 kHz vs. playbacks in which that signal energy has been filtered out, someone needs to capture and analyze the sound that the listeners are hearing, to find out whether it contains significant distortion artifacts below 20 kHz or not.)

In the case that you show, there is an enormous rolloff which is probably in the program material itself. I say that because it is already quite steep in the midrange. By 20 kHz, there would have been nothing significant to filter out anyway. I see no point in mourning for what isn't there, especially when we couldn't have heard it if it had been there. The part of a recording to be concerned about is the part that playback systems can reproduce, and that human beings can hear.

--best regards
« Last Edit: April 05, 2015, 07:35:36 PM by DSatz »
music > microphones > a recorder of some sort

Offline vanark

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Re: Frequency analysis
« Reply #4 on: April 05, 2015, 08:00:50 PM »
I'm pretty sure the OP is speaking about a conversion to mp3 ("lossy") and then a reconversion back to WAV. From my experience, those graphs do not represent lossy material, but I prefer to do that type of thing myself. Since you are the originator of the files, I'm at a loss as to why you think they are lossy. I've never looked at the bit rate assigned to the flac so I have no idea what that represents. WAV to FLAC conversion ratio can depend on several factors, including music content and the "stereo-ness" of the two channels. Mono recordings, or recordings that have very similar sonic quality in both channels , will compress at a higher ratio than true stereo files. A low volume acoustic performance will compress at a higher ratio as well.

If you posted a small snippet of the actual WAV file, you might get some of us to give you a better feel for it. If you do, please make sure it is from the middle of a song with usual musical content.
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Offline Andrea82

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Re: Frequency analysis
« Reply #5 on: April 06, 2015, 03:58:35 AM »
Thank DSatz and vanarz for the detailed explanations.
Here you can download a 1 minute sample from the master 24-96 (I only add 9DB, because the original vol was low).
https://www.dropbox.com/s/n0gx258dwa8e7o2/untitled.wav?dl=0

Thank you

 

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