Loudness Penalty: Find out if audio will be turned down by streaming services
loudnesspenalty.com
loudnesspenalty.com
Self-plug: A while back I reverse-engineered the DR algorithm and implemented it as a Python script. It's [DRmeter on GitHub](https://github.com/janw/drmeter).
From what I quickly gathered from the specs^1, Replay Gain (RG) and Dymanic Range (DR) are indeed similar in the grand scheme of things. Both algorithms employ percentile-based statistic of RMS values. While RG is determined by the 95% percentile of RMS values on 50ms audio frames, DR uses the 80% percentile on 3-second-long audio frame RMS values. So RG is definitely on the side of short-term analysis, while DR is long-term.
What differentiates RG more plainly though is its stronger psycho-acoustical foundation in regards to frequency response: It applies a so-called "Loudness filter" (modelled after the Equal-Loudness contour^2 found in human hearing) before doing the RMS statistics. The Equal-Loudness contour (also known as "Isophone" where I come from) is in turn modelled after non-linear response of the ear to sound pressure levels in relation to the frequency. It basically adjusts for what in layman's terms I'd call "Importance" of the different ranges.
Therefore I'd say RG is very much focused on what human hearing will perceive as loud (too loud, or just loud enough), while DR focuses on "exposing offenders in all ranges of the spectrum". My educated guess would be: Loud bassy sounds would not harm an RG score, while having a significant impact on the DR, as its not attenuating low frequencies.
Would be interesting to see a comparison of the two!
[1]: http://wiki.hydrogenaud.io/index.php?title=ReplayGain_specif...
Cons: each playback means bandwidth + royalties cost.
So the question is, does the probability times the return from their friends bring more money than the free playbacks? I'd really like to know the answer.
The "give us your email address for more information" part also seems slimy.
"Since streaming services are going to turn loud music down anyway, more and more people are deciding they would prefer to take control of this process themselves, and optimize their music for the best possible results."
and
"We recommend avoiding very large negative LP values, especially on YouTube because songs like this often sound “smaller” than those with LP scores closer to zero.
Hear it for yourself For example, compare the loud sections of these two Metallica songs on YouTube - The Day That Never Comes (LP -5.8)[1] and Hardwired (LP -2.4)[2]. Which has more impact?
Loudness normalization means you have the opportunity to make your music sound better, too. In our experience, LP between 0 and -2 on YouTube will work well for even the loudest genres. For example, Drake’s recent hit God’s Plan has a score of LP -0.8 on YouTube, and it sounds huge."
[1]: https://youtu.be/dkNfNR1WYMY [2]: https://www.youtube.com/watch?v=uhBHL3v4d3I&feature=youtu.be [3]: https://www.youtube.com/watch?v=xpVfcZ0ZcFM&feature=youtu.be
Lars thought it was great.
[0] http://recordinghacks.com/2008/12/20/metallica-wins-the-loud...
This was done for decades by radio stations applying strong compression, because they knew that someone going from frequency to frequency was more likely to stop on a station that sounded loud, implying that they were getting a stronger signal and could listen to it longer before they drove out of range. The longer the listener stayed on their station, the more ad impressions. But then the record labels started doing it and so even buying a CD meant you were getting a lower-quality album.
A few years ago Apple mandated the use of their Sound Check tool that penalizes iTunes Radio songs that are all-loud, all-the-time. And it sounds (no pun intended) that Spotify and other services followed their lead.
Google cache of article because the site is unresponsive:
http://webcache.googleusercontent.com/search?q=cache:P4y5VeS...
Spotify used to normalize to -11 LUFS, but more recently has migrated to -14, which other streaming services already use and seems to be becoming the standard. For my new album that was just released, I mastered to about -11 to -13 LUFS, which tends to be loud enough to still stand out un-normalized, but is close enough to target that it doesn’t take a noticeable hit on normalization.
The album version is compressed to hell but the version that shipped with Guitar Hero has none of that extra compression, presumably because someone who wasn't deaf mixed it.
The difference is night and day.
Dynamic range is good...
In fact, if music producers stopped trying to make their music so loud, there would be more room for dynamic range in the music. The goal of this site seems to be that they wouldn't mix a whole song to be top volume, since it won't play any louder most places anyway. This in turn could lead to the return of using more dynamic range. I have my doubts that this will actually happen.
Listen to a good recording of something like The William Tell Overture and you should notice that the quiet parts are less than 10% or so of volume of the loud parts.
Listening to that Dire Straits album really illustrates the point.
Limiting is about turning down the music when it peaks above a certain threshold measured in decibels, and loudness normalisation is about normalising music to its perceived loudness, measured in LUFS.
Back then these records were made to be played back on big hi-hi systems. Big speakers that filled the room and were placed far away from the listener. This is not a standard setup today. You're more likely to see music played from wimpy TV speakers, headphones or earbuds.
Background article on Loudness Race https://en.wikipedia.org/wiki/Loudness_war
For the raw sample data it's also kind of inevitable to use a linear scale when you want different sounds to add nicely, if you use a logarithmic scale then adding two sounds would distort them, which isn't ideal. When using a linear scale you can hide the quantization noise pretty easily with dither which just sounds like you're adding white noise.
I am unaware of any audio program which internally represents audio in dB. Waveform displays default to linear scales, though logarithmic scaling is usually available. Just about the only place where logarithmic scales are the default is frequency domain graphical representations like spectrograms.
Rescaling to dB, a logarithmic unit, both better mirrors how humans hear, and brings the numbers under control, 0-135dB is nicer.
But at least for me, I like capturing and storing in a Pascal-ish unit, because I'd rather capture pressure linearly and convert to human-interpretable log units where needed. If nothing else, because things like waveform addition are a bit more straightforward mentally on linear scales. Folks have made other decisions in some formats, but I've never found it compelling.