Posts Tagged loudness
Lots of ink has been spilled about the Loudness war and how modern recordings keep getting louder as a cheap method of grabbing a listener’s attention. We know that, in general, music is getting louder. But what are the loudest songs? We can use The Echo Nest API to answer this question. Since the Echo Nest has analyzed millions and millions of songs, we can make a simple API query that will return the set of loudest songs known to man. (For the hardcore geeks, here’s the API query that I used). Note that I’ve restricted the results to those in the 7Digital-US catalog in order to guarantee that I’ll have a 30 second preview for each song.
So without further adieu, here are the loudest songs
The song Topping and Core by Grmalking555 has a whopping loudness of 4.428 dB.
The song Modifications by Micron has a loudness of 4.318 dB.
The song Hey You Fuxxx! by Kylie Minoise with a loudness of 4.231 dB
Here’s a little taste of Kylie Minoise live (you may want to turn down your volume)
The song War Memorial Exit by Noma with a loudness of 4.166 dB
The song Hello Dirty 10 by Massimo with a loudness of 4.121 dB.
These songs are pretty niche. So I thought it might be interesting to look the loudest songs culled from the most popular songs. Here’s the query to do that. The loudest popular song is:
The loudest popular song is Welcome to the Jungle by Guns ‘N Roses with a loudness of -1.931 dB.
You may be wondering how a loudness value can be greater than 0dB. Loudness is a complex measurement that is both a function of time and frequency. Unlike traditional loudness measures, The Echo Nest analysis models loudness via a human model of listening, instead of directly mapping loudness from the recorded signal. For instance, with a traditional dB model a simple sinusoidal function would be measured as having the same exact “amplitude” (in dB) whether at 3KHz or 12KHz. But with The Echo Nest model, the loudness is lower at 12KHz than it is at 3KHz because you actually perceive those signals differently.
Thanks to the always awesome 7Digital for providing album art and 30 second previews in this post.
Evanescence is one of my guilty listening pleasures. I enjoy how Amy Lee’s voice is juxtaposed against the wall of sound produced by the rest of the band. For instance, in the song Imaginary, there’s a 30 seconds of sweet voice + violins before you get slammed by the hammer of the gods:
This extreme change in energy makes for a very dramatic moment in the music. It is one of the reasons that I listen to progressive rock and nu-metal (despite the mockery of my co-workers). However, finding these dramatic gems in the music is hard – there’s a lot of goth- and nu-metal to filter through, and much of it is really bad. After even just a few minutes of listening I feel like I’m lost at a Twicon. What I need is a tool to help me find these dramatic moments, to filter through the thousands of songs to find the ones that have those special moments when the beauty comes eye to eye with the beast.
My intuition tells me that a good place to start is to look at the loudness profile for songs with these dramatic moments. I should expect to see a sustained period of relatively soft music followed by sharp transition to a sustained period of loud music. This is indeed what we see:
This plot shows a windowed average of the Echo Nest loudness for the first 50 seconds of the song. In this plot we see a relatively quiet first 10 seconds (hovering between -21 and -18 db), followed by an extremely loud section of around -10db). (Note that this version of the song has a shorter intro than the version in the Youtube video). If we can write some code to detect these transitions, then we will have a drama detector.
The Drama Detector: Finding a rising edge in a loudness profile is pretty easy, but we want to go beyond that and make sure we have a way to rank then so that we can find the most dramatic changes. There are two metrics that we can use to rank the amount of drama: (1) The average change in loudness at the transition and (2) the length of the quiet period leading up to the transition. The bigger the change in volume and the the longer it has been quiet means more drama. Let’s look at another dramatic moment as an example:
The opening 30 seconds of Blackest Eyes by Porcupine Tree fit the dramatic mold. Here’s an annotated loudness plot for the opening:
The drama-finding algorithm simply looks for loudness edges above a certain dB threshold and then works backward to find the beginning of the ‘quiet period’. To make a ranking score that combines both the decibel change and the quiet period, I tried the simplest thing that could possible work which is to just multiply the change in decibels by the quiet period (in seconds). Let’s try this metric out on a few songs to see how it works:
- Porcupine Tree – Blackest Eyes – score: 18 x 24 = 432
- Evanescence – Imaginary (w/ 30 second intro) – score: 299
- Lady Gaga – Poker Face- score: 82 – not very dramatic
- Katy Perry – I kissed a girl – score: 33 – extremely undramatic
This seems to pass the sanity test, dramatic songs score high, non-dramatic songs score low (using my very narrow definition of dramatic). With this algorithm in mind, I then went hunting for some drama. To do this, I found the 50 artists most similar to Evanescence, and for each of these artists I found the 20 most hotttest songs. I then examined each of these 1,000 songs and ranked them in dramatic order. So, put on your pancake and eye shadow, dim the lights, light the candelabra and enjoy some dramatic moments
First up is the wonderfully upbeat I want to Die by Mortal Love. This 10 minute long song has a whopping drama score of 2014. There a full two minutes of quiet starting at 5 minutes into the song before the dramatic moment (with 16 dB of dramatic power!) occurs:
The dramatic moment occurs at 7:12 seconds into the song – but I’m not sure if it is worth the wait. Not for me, but probably something they could play at the Forks Washington High School prom though.
The song Jillian by Within Temptation gets a score of 861 for this dramatic opening:
Now that’s drama! Take a look at the plot:
The slow build – and then the hammer hits. You can almost see the vampires and the werewolves colliding in a frenzy.
During this little project I learned that most of the original band members of Evanescence left and formed another band called We are the Fallen – with a very similar sound (leading me to suspect that there was a whole lot of a very different kind of drama in Evanescence). Here’s their dramatic Tear The World Down (scores a 468):
Finally we have this track Maria Guano Apes – perhaps my favorite of the bunch:
Update: @han wondered how well the dramatic detector faired on Romantic-era music. Here’s a plot for Berlioz’s Symphony Fantastique: March to the Scaffold:
This gets a very dramatic score 361. Note that in the following rendition the dramatic bit that aligns with the previous plot occurs at 1:44:
Well – there you have it , a little bit of code to detect dramatic moments in music. It can’t, of course, tell you whether or not the music is good, but it can help you filter music down to a small set where you can easily preview it all. To build the drama detector, I used a few of The Echo Nest APIs including:
- song/search – to search for songs by name and to get the analysis data (where all the detailed loudness info lives)
- artist/similar – to find all the similar artists to a seed (in this case Evanescence)
The code is written in Python using pyechonest, and the plots were made using gnuplot. If you are interested in finding your own dramatic bits let me know and I’ll post the code somewhere.