If we asked you to describe the vibe of your favourite nightclub, could you? Today, we show you how we would describe the sounds of some of our favourite clubs, with the help of the Cyanite music AI analysis software. 

We analysed album compilations of 9 well-loved clubs across Germany. From Berlin, these were Berghain, Griessmühle, About Blank, Golden Gate and Kater Blau. In addition to these, we analysed music from Hamburg’s Golden Pudel, Leipzig’s Institut für Zukunft, and Omen and Robert Johnson in Frankfurt. 

The mood multi-label classifier provides the following labels:

tense, uplifting, relaxing, melancholic, dark, energetic, happy

Each label has a score reaching from 0-1, where 0 (0%) indicates that the track is unlikely to represent a given mood and 1 (100%) indicates a high probability that the track represents a given mood.

Since the mood of a track might not always be properly described by a single tag, the mood classifier is able to predict multiple moods for a given song instead of only one. A track could be classified with dark (Score: 0.9), while also being classified with aggressive (Score: 0.8).

The mood can be retrieved both averaged over the whole track and segment-wise over time with 15s temporal resolution. In addition the score the API also exposes a list which includes the most likely moods, or the term ambiguous in case of none of the audio not reflecting any of our mood tags properly.

Insights from Instrumental and Voice analysis: Berlin clubs lead the way for greatest use of Instrumental in their tracks.

Based on results from the CYANITE Instrument and Voice machine learning analysis, we see that while most of these club compilations’ tracks are extremely dominated by instrumentals, the top four clubs which contained the most instrumental-heavy tracks were from Berlin. 

About Blank contained the highest amount of instrumental, followed by Griessmühle, Berghain and Golden Gate. For all of these clubs, our analysis showed that instrumentals made up more than 80% of the tracks. 

When we look at results of the voice analysis, we see that the clubs with the most use of female voices in their tracks are clubs outside of Berlin. In first place, we have Institut für Zukunft, followed by Omen, and then Golden Pudel. Funny enough, we also found that the four clubs with the least use of female vocals in their tracks were from Berlin! These clubs are: Kater Blau, About Blank, Griessmühle, and Golden Gate. 

When looking at the presence of male vocals, we see that Golden Pudel is the club using the most male vocals amongst the clubs we are studying today. This is followed by Omen and Golden Gate. 

Based on the results from this analysis, data from Golden Pudel intrigued us the most. We observe that Golden Pudel’s music, unlike the rest of the clubs, has a slightly more even balance between instrumental and vocals that is almost a 50/50 split. 

Insights from the CYANITE mood tagging technology: Berghain is the gloomiest of them all. 

Looking at the results, here’s what we found: 

With its grim industrial aesthetic, it’s fitting that our analysis found Berghain to be the most melancholic club. Berghain ties with Institut für Zunkunft for having the most Dark sound. 

Golden Gate, a favourite of ours for a good night of House music, takes the prize for being the most uplifting club. Our mood analysis also showed that Frankfurt’s Omen club is at once the most tense and most energetic, while Golden Pudel in Hamburg was found to be the most happy and relaxing. Our mood analysis also showed that the compilation from Frankfurt’s now-defunct Omen club, is at once the most tense and most energetic out of all the clubs’ compilations. A very apt result indeed- Omen was a prominent symbol of the unrestrained, pure fervour of 90’s rave culture, and one whose sound we definitely miss greatly.

Talking about the ‘Berlin Sound’…

Comparing the clubs, we see that clubs in Berlin have a distinct, extreme skew towards the dark and melancholic, indicating the very characteristic moodiness that we so love and miss in these times!

Looking at the clubs elsewhere, we see that while dark and melancholic moods are still very much present, there isn’t as clear of a skew towards these two only. Instead, our data from the 4 clubs outside of Berlin show more diverse moods, with no clear skew in a certain direction. 

Genre Tagging with our music AI: Some interesting insights 

We see that for Berlin clubs, the CYANITE AI analysis of their club compilations reveals a strong skew towards Techno and Tech House. The top 3 places with the most amount of Techno in their songs are: in top place, About Blank, followed by Berghain, and then Griessmühle. For Tech House, the top 3 clubs are Golden Gate, Kater Blau, and About Blank. 

Outside of Berlin, we see a more varied mix of genres in the club compilations. Omen ranks highest in the amount of trance in the selection, a genre that was almost not found at all in the Berlin clubs we studied.  

You can listen to some of the compilations we analysed here:

About blank: :// About Blank ( 2018) , :// About Blank 002 (2017), :// About Blank 004 (2018), :// About Blank 006 ( 2019) and :// About Blank 007 (2019) 

Kater Blau: Katermukke 150 Compilation (2017)

Berghain / Panorama Bar: Ostgut Ton – Zehn (2015)

Golden Gate: Compilation (2012)

Golden Pudel: Operation Pudel (2001)

Omen: Moka DJ Compilation (1996)

Institut Fur Zukunft : Various 5IVE ( 2019)

Robert Johnson:  Livesaver Compilation 2 (2015) & Livesaver Compilation 3 (2017)

Overall, our quick research into these clubs with AI showed us some very interesting things. It seems that with a larger data set, it might be possible to quantify the Berlin sound and perhaps also sounds for other key party cities.

For more Cyanite content on AI and music, check these out:

Translating Sonic Languages: Different Perspectives On Music Analysis

Ellen Allien, Roman Flügel and Dub Isotope: An AI Analysis of Techno and Drum ‘n’ Bass

Podcast: Our Data Scientist Roman about the potential and challenges of AI in music

As a team of music lovers, the Cyanite team has been tuning in regularly to Berlin’s lockdown livestream DJ sets over the last few months. 

Some of us might be of the opinion that recording technology should be kept firmly away from the dancefloor in order for party people to truly revel in the night’s atmosphere. Right now, it seems the opposite is true. 

These livestream recordings have made it possible for music fans in Berlin (and the world) to experience electronic music and to feel connected to the electronic music community. Technology has proven itself as very much needed and welcome in the music space, and in this case, instrumental in keeping club culture alive during the coronavirus restrictions.

Decoding Electronic Music with AI

In this spirit of club culture, we ran some of our favourite mixes through our analysis models.

Set #1: Ellen Alliens’s Griessmuehle set

A heavyweight in the techno scene, Ellen Allien’s combination of classic techno with a side of experimental and IDM is one-of-a-kind, and a definite favorite at Cyanite. 

In this set, techno alternated between dancey and contemplative. Our genre analysis results revealed that the set was predictably profiled as consisting mostly of “electronic dance”. In moments where the electronic dance genre was detected at a low level, the ambient genre was inversely detected as the dominant genre.

Looking at our emotion analysis results, the top quality detected in her hour-long set was “dark”. This was followed closely by “tense”, and then “energetic”. Characteristically, we observed that her set opened with the level of darkness at a high point, before hovering at a more or less at a consistent mid-to-high level after, before ending high again. 

Tenseness, however, was a different story altogether. In Ellen Allien’s set, techno is a tightrope walk. Listeners alternate between feeling almost about to tip over the edge and occasional moments of stability at the peak.

Sustained periods of high musical tension were found at the beginning, middle, and end of her set. Outside of those intervals, the level of tenseness peaked and plunged all throughout the set, often in sharp, spiky drops and rises. 

In her set, tension is also characterized by a frenetic level of energy: we saw that the level of energy detected very closely paralleled the pattern of tenseness.

Set #2: Roman Flügel’s Wilde Renate stream 

Roman Flügel’s Wilde Renate stream is another hot favorite. 

While the Ellen Allien set we listened to earlier veered towards the heavier side, this set takes us to a gentler side of techno. Flügel treated our ears to an hour of electro, techno and occasional ambient. 

A softer brand of techno does not mean happy techno though (if there can ever be such a concept). While the previously discussed set was ruled by high-strung techno energy, Flügel’s set is more muted. 

Topmost of the qualities detected was ‘melancholia’. The atmosphere of melancholy hovered at a consistently high level throughout the entire set, with brief intervals of dips. In those moments where melancholy dropped, tenseness – which was at a base level throughout most of the set, climbed up slightly. 

Almost as much as his set was melancholic, it was calm. The smooth melodies and synth swells in the set gave it an air of sereneness. Calmness was the second highest quality detected. The level of calm closely mirrored the level of melancholy throughout the set, although it had more well-defined plateaus during the most calm moments. 

Flügel’s set was also comfortingly brooding (exactly how we love our techno). Underscoring the calmness and melancholy was darkness, which was profiled as the third top quality in the set. 

The haunting, sad effect of minor keys seem to be well favored in techno. 

Both these techno sets were detected to be mostly in minor keys: Ellen Allien’s one was predominantly B Flat minor, and Roman Flügel’s in F minor.

Set #3: Dub-Isotope’s VOID mix 

Pivoting away from techno, our third set analyzed was a Drum N Bass one. We analyzed Dub Isotope’s set at VOID Berlin- a stellar venue for non-techno and techno music alike. 

While the two sets above were in a minor key, our analysis results showed that this set favored F major. Also, compared to the 105-130 BPM range of the techno sets, Dub Isotope’s set sat firmly at 171 BPM, a tempo characteristic of Drum N Bass music. 

Listening to Drum N Bass is quite a diverse emotional journey. The qualities detected in this set were at more moderate levels, compared to the earlier two techno sets. 

Our results signaled to us that this set was definitely more upbeat. While the techno sets at certain emotions at a distinctively high level, and others at a significantly lower range (e.g. Relaxing’ at near rock bottom levels for both), the various emotions detected for Dub Isotope’s set mostly occupied the mid-range. Among these, the top few to note were ‘calm’, ‘dark’ and ‘relaxing’, followed very closely by happiness. 

Looking at our genre analysis, Dub Isotope’s set was similarly detected to be electronic dance, with an interesting spurt of hip hop just a bit after the halfway mark of the mix

Analyze your own music

We built Cyanite in a way that everyone can use it to analyze their own music with AI. If you want to get insights on mood, genre, bpm, and key for your music, you can register here for free and try it out yourself. Contact us if you have feedback, ideas, or want to use our API to integrate Cyanite into your database.

For more of our thoughts on Artificial Intelligence and Music Catalogues, check these out:

3 Reasons Music Catalogues Should Embrace AI Innovation During The Corona Quarantine

Free White Paper: 8 Tips How To Organize Your Music Catalog Better

4 Technology Trends Music Catalogue Owners Need To Know