Nina Kraviz — @ Dommune (2015)
Experimental Techno · 1h 57m · analysed 18 Aug 2026 · source: soundcloud.com
Public mix analysis — no affiliation or endorsement. This report measures a publicly available recording hosted on soundcloud.com. The scores are produced by SOONOS and do not imply any partnership with, or approval by, Nina Kraviz.
In short
@ Dommune (2015) by Nina Kraviz scores 60/100 in the SOONOS analysis (developing). The strongest dimension is IDENTITY (93/100) and the weakest is TECHNIQUE (81/100).
This DJ understands that in techno, the silence between the drums is as important as the drums themselves.
Key takeaways
What worked
- Technical precision in transitions.
- Exceptional groove maintenance.
- Confident and consistent track selection.
What weakened the set
- Long static loops (6×) — Sections sitting on the same loop without layering, EQ moves or tension shifts (12:00, 20:00, 27:00, 47:00, 53:00, 59:00). Long loops kill dancefloor momentum.
- Beat alignment needs work — typical drift of 30 ms — Measured median beat-grid drift is 30 ms across the transitions. Reference: pro ≤ 25 ms, needs work 30-42 ms, must be reworked > 42 ms. Above ~30 ms the kick flams and dancers feel the blend slipping.
What to try next
- Experiment with very short (1-beat) silences to reset the listener's ear.
- Use a high-pass filter more aggressively on the outgoing track to create a 'lifting' sensation before the new kick hits.
- Consider a slightly more varied percussive palette in the next segment to maintain long-term interest.
- Experiment with wider stereo imaging for atmospheric layers to enhance the sense of space.
Timestamped insights
Each moment below is tagged with how it was produced: “measured” comes from the DSP pass on the audio, “listening” comes from the multi-agent listening pass.
Perfectly executed blend where the incoming bassline takes over without any phase issues.
Smooth transition using high-end elements to bridge the tracks before the low-end swap.
Perfectly executed handover. The incoming kick is phased correctly and takes over the sub-frequencies without any volume dip.
The DJ layers a new rhythmic element for 32 bars before slowly fading out the previous track's mids. Very professional.
A textbook hypnotic techno transition. The incoming percussive loop is introduced so subtly that the listener barely notices the change until the low-end swap at the phrase boundary.
About this experimental techno set
@ Dommune (2015) is a experimental techno DJ set by Nina Kraviz, running 1h 57m. It was measured by the SOONOS multi-agent engine and scores 60/100 overall — developing.
The engine files this performance as “Promising”.
This DJ understands that in techno, the silence between the drums is as important as the drums themselves.
How the score breaks down
SOONOS scores this set across 5 weighted categories. The strongest is IDENTITY at 93/100; the weakest is TECHNIQUE at 81/100.
The final score is capped by measured beatmatching: the DSP layer overrides the listening layer whenever it measures an execution issue directly in the audio.
Analysis coverage for this file is 100% — the share of the set the engine could measure with full confidence.
Energy and structure
The energy curve was sampled at 54 points, moving between 70 and 94 on the SOONOS energy scale — a moderate dynamic range across the set.
5 transitions were detected and scored individually.
Beat-grid measurement (DSP) reports 331.1 grid breaks per hour, with a median beat offset of 30 ms.
How this score is built
Measured layer (DSP): the audio file is analysed directly — beat grid, tempo stability, loudness and energy. These values are measurements, not opinions.
Listening layer: a multi-agent pass reads musical intent — programming, storytelling, coherence and crowd effect. This layer interprets, it does not measure.
Fusion and ceilings: the two layers are merged, and the measured layer always wins on execution. When the DSP hears an execution problem, it caps the final score even if the listening layer is positive.
On this set, the ceiling applied is measured beatmatching.
Measured coverage for this file is 100% of the set.
Full SOONOS analysis
This DJ understands that in techno, the silence between the drums is as important as the drums themselves.
The 8 dimensions
Not available — the 8-dimension profile was not measured for this set.
Score breakdown
TECHNIQUE
How well did you execute?
25%81
TECHNIQUE
How well did you execute?
STORYTELLING
Did the mix go somewhere?
25%89
STORYTELLING
Did the mix go somewhere?
ENERGY
Did you control the room?
20%84
ENERGY
Did you control the room?
SURPRISE
Did you remain unpredictable?
15%82
SURPRISE
Did you remain unpredictable?
IDENTITY
Did the mix sound like you?
15%93
IDENTITY
Did the mix sound like you?
Final score capped by measured beatmatching — the weighted average before the cap was 85.
Energy arc
Transitions analysed (5)
Long EQ blend with low-end handover
Perfectly executed blend where the incoming bassline takes over without any phase issues.
Percussive layering and high-pass filter sweep
Smooth transition using high-end elements to bridge the tracks before the low-end swap.
Long EQ blend with low-end swap
Perfectly executed handover. The incoming kick is phased correctly and takes over the sub-frequencies without any volume dip.
Additive layering
The DJ layers a new rhythmic element for 32 bars before slowly fading out the previous track's mids. Very professional.
Long EQ blend with low-end swap
A textbook hypnotic techno transition. The incoming percussive loop is introduced so subtly that the listener barely notices the change until the low-end swap at the phrase boundary.
Technical subscores
88
EQ balance
93
Beat alignment
89
Energy control
92
Tempo stability
88
Loudness control
89
Musical coherence
86
Harmonic compatibility
89
Transition cleanliness
Measured (DSP)
30 ms
Beat-grid drift (median)
Typical gap between the two tracks' beats while they play together. Lower is tighter.
137 ms
Drift p95
Worst-case drift: 95% of the set stays tighter than this value.
7,015
Boundaries detected
Points where the audio changes track or section.
26
Hard cuts / h
Abrupt track changes per hour, with no blend between the two records.
46
Clipping events
Moments where the recording hits the ceiling and distorts.
692
Level jumps
Sudden volume steps between tracks.
Measurement confidence 100% · analysed on the full audio.
Recurring patterns
Long static loops (6×)
Sections sitting on the same loop without layering, EQ moves or tension shifts (12:00, 20:00, 27:00, 47:00, 53:00, 59:00). Long loops kill dancefloor momentum.
Beat alignment needs work — typical drift of 30 ms
Measured median beat-grid drift is 30 ms across the transitions. Reference: pro ≤ 25 ms, needs work 30-42 ms, must be reworked > 42 ms. Above ~30 ms the kick flams and dancers feel the blend slipping.
What SOONOS heard
- Technical precision in transitions.
- Exceptional groove maintenance.
- Confident and consistent track selection.
Timeline
- 05:20Groove Lock Peak
- 11:10Tension Plateau
- 16:30Groove Lock Peak
- 21:15Sub-Bass Transition
- 24:20Hypnotic Lock-In
- 29:30Texture Evolution
Coaching notes
- Experiment with very short (1-beat) silences to reset the listener's ear.
- Use a high-pass filter more aggressively on the outgoing track to create a 'lifting' sensation before the new kick hits.
- Consider a slightly more varied percussive palette in the next segment to maintain long-term interest.
- Experiment with wider stereo imaging for atmospheric layers to enhance the sense of space.
- Use subtle delay throws on percussive elements to create rhythmic 'ghost' notes.
- Consider a brief, beatless atmospheric bridge to reset the listener's ear before a major energy shift.
- Continue to trust your restraint; the long blends are your signature strength.
- Experiment with very subtle melodic elements to add a layer of emotional depth to the industrial textures.
- Consider a brief 'reset' moment every 20-30 minutes to keep the listener's ears fresh for the next hypnotic cycle.
- Maintain the exceptional focus on rhythmic layering; it is your strongest asset.
- During vinyl transitions, be slightly more aggressive with the mid-frequency cuts to avoid brief sonic clutter.
- Experiment with one 'wildcard' track that breaks the industrial palette to add a narrative surprise.
- Introduce a final melodic or atmospheric element to provide a stronger sense of closure.
- Experiment with brief moments of silence or breakdowns to reset the tension.
- Maintain the exceptional technical precision shown in the EQ blends.
Curious how your own set scores?
Methodology and limitations
This report is produced automatically from the published recording. It measures what is present in the audio file: a bad source encoding, a partial upload or a heavily processed broadcast version can change the measured values. Nothing here reflects the room, the crowd or the night itself.
Read the full SOONOS methodology →Questions about this analysis
- What score does Nina Kraviz's @ Dommune (2015) get?
- @ Dommune (2015) scores 60/100 in the SOONOS Mix Database (developing), based on audio measurement plus multi-agent listening.
- How long is @ Dommune (2015)?
- The analysed recording runs 1h 57m.
- Which part of the mix scores best?
- IDENTITY is the strongest category at 93/100, while TECHNIQUE is the lowest at 81/100.
- How is this score calculated?
- SOONOS measures the audio with a DSP pass (beat grid, loudness, tempo, energy) and runs a multi-agent listening pass on top. Measured axes always override the listening layer, so an execution issue heard in the file caps the final score.
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Test how a set like this one would land in a club, a beach club or a festival.
Get the same breakdown on your own set: transitions, energy arc and measured execution.
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