DosemDosem @ Womb Tokyo 2025

    Melodic Techno · 1h 30m · analysed 22 Aug 2026

    Overall score
    84/100
    Level
    club ready
    Duration
    1h 30m
    Genre
    Melodic Techno

    About this melodic techno set

    Dosem @ Womb Tokyo 2025 is a melodic techno DJ set by Dosem, running 1h 30m. It was measured by the SOONOS multi-agent engine and scores 84/100 overall — club ready.

    The engine files this performance as “Promising”.

    You mix with the confidence of someone who knows exactly where the story is going.

    How the score breaks down

    SOONOS scores this set across 5 weighted categories. The strongest is IDENTITY at 90/100; the weakest is SURPRISE at 81/100.

    The final score is capped by measured -: 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 31 points, moving between 30 and 90 on the SOONOS energy scale — a wide dynamic range across the set.

    6 transitions were detected and scored individually.

    Beat-grid measurement (DSP) reports 511.1 grid breaks per hour, with a median beat offset of 22 ms.

    Listen to the original set

    Full SOONOS analysis

    TECSELNRGCRWHRMGRVCRESIG
    0

    You mix with the confidence of someone who knows exactly where the story is going.

    The 8 dimensions

    Technical precision0
    Track selection0
    Energy arc0
    Crowd control0
    Harmonic depth0
    Groove patience0
    Creativity0
    Signature0

    Score breakdown

    TECHNIQUE

    How well did you execute?

    25%82
    Beat Alignmentmeasured79
    Transition Qualitymeasured73
    Phrase Accuracymeasured93
    EQ & Frequency Control (estimated)measured88
    Tempo Stability (estimated)measured96
    Technical Cleanlinessmeasured54

    STORYTELLING

    Did the mix go somewhere?

    25%88
    Narrative ArcAI92
    ProgressionAI87
    Tension & ReleaseAI84
    Section AwarenessAI88
    Flow ContinuityAI93
    PayoffAI84

    ENERGY

    Did you control the room?

    20%86
    Energy Curvemeasured85
    PacingAI88
    MomentumAI91
    Peak ManagementAI84
    Energy HandoffAI86
    Fatigue ControlAI77

    SURPRISE

    Did you remain unpredictable?

    15%81
    Unexpected MomentsAI78
    ContrastAI80
    Transition Varietymeasured91
    Selection RiskAI79
    FreshnessAI74
    Surprise ControlAI78

    IDENTITY

    Did the mix sound like you?

    15%90
    Selection QualityAI88
    Identity ConsistencyAI96
    IntentionalityAI91
    ConfidenceAI90
    RestraintAI87
    SignatureAI85

    Final score capped by measured execution (-) — weighted average was 85.

    Energy arc

    00:0090:00

    Transitions analysed (6)

    02:15

    Long EQ blend with high-pass filtering

    A textbook melodic techno blend. The incoming track's atmosphere is introduced so subtly it feels like a natural evolution of the first track.

    94
    06:58

    Bass-swap on phrase boundary

    Clean energy handoff. The DJ waits for the perfect phrase end to swap the low-end, maintaining the groove without a hiccup.

    90
    11:45

    Long EQ blend with low-end swap

    A textbook melodic techno transition. The incoming track's sub-bass is introduced so subtly it feels like a natural evolution of the previous track.

    92
    18:20

    Melodic layering and filter fade

    Excellent use of harmonic compatibility to layer two melodic themes before fading the outgoing track's highs.

    88
    24:12

    Perfect Blend

    100
    29:12

    Seamless EQ Swap

    100

    Technical subscores

    88

    EQ balance

    95

    Beat alignment

    88

    Energy control

    96

    Tempo stability

    85

    Loudness control

    92

    Musical coherence

    92

    Harmonic compatibility

    91

    Transition cleanliness

    Measured (DSP)

    21.9 ms

    Beat-grid drift (median)

    215.5 ms

    Drift p95

    5,389

    Boundaries detected

    78

    Hard cuts / h

    35

    Clipping events

    139

    Level jumps

    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 (20:00, 34:00, 40:00, 44:00, 51:00, 87:00). Long loops kill dancefloor momentum.

    Timeline

    • 00:45Atmospheric Immersion
    • 09:15Groove Lock
    • 14:30Melodic Expansion
    • 20:15Groove Re-entry

    Coaching notes

    • Continue to prioritize harmonic mixing; it is a key part of your sound.
    • Experiment with shorter, more aggressive transitions to create contrast.
    • Use more atmospheric FX to bridge the gaps between melodic themes.
    • Experiment with more aggressive filter work to create sharper tension points.
    • Incorporate a few tracks with more distinct vocal or lead elements to break the percussive focus.
    • Try slightly shorter transitions in specific sections to increase the perceived energy.
    • Experiment with more aggressive filter work to add a 'live' feel to the long blends.
    • Incorporate a signature 'outro' element (vocal or unique FX) to leave a lasting impression.
    • Maintain this level of technical precision while taking slightly more risks with track selection in the mid-set.
    Listen on SoundCloud

    Curious how your own set scores?

    Questions about this analysis

    What score does Dosem's Dosem @ Womb Tokyo 2025 get?
    Dosem @ Womb Tokyo 2025 scores 84/100 in the SOONOS Mix Database (club ready), based on audio measurement plus multi-agent listening.
    How long is Dosem @ Womb Tokyo 2025?
    The analysed recording runs 1h 30m.
    Which part of the mix scores best?
    IDENTITY is the strongest category at 90/100, while SURPRISE 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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