Mixing with Measurement

A workflow for using Phantom as a measurement companion during mixing. Instead of guessing whether your EQ moves worked or your compression is appropriate, measure the results and iterate with data.

When to use this

  • During active mixing sessions when you want verification
  • After making EQ/compression moves — “did that actually help?”
  • When your ears are fatigued and you need objective data
  • Checking mix balance between sections (verse vs chorus)

Workflow Overview

1

Set measurement checkpoints

Capture the state before processing so you can measure improvement

2

EQ with masking data

Use Phantom's masking analysis to guide surgical EQ decisions

3

Verify dynamics after compression

Confirm you haven't over-compressed by checking crest factor and range

4

Check stereo image and phase

Ensure your panning and spatial processing translate to mono

5

Compare mix versions

A/B your current mix against previous versions with actual measurements

Step 1: Set measurement checkpoints

Why: Before making any processing changes, capture baseline measurements. This lets you objectively compare “before” and “after” instead of relying on memory (which is unreliable after 30 minutes of listening).

Prompt:

Run a full diagnostic on my current mix bus at mix-v1-unprocessed.wav — I’m about to start processing and want a baseline

Phantom output:

Full Diagnostic: mix-v1-unprocessed.wav Duration: 3:42 | 44.1kHz/24bit | Stereo

Spectral Centroid: 2,456 Hz Rolloff: 10.8 kHz

Loudness Integrated: -18.2 LUFS True peak: -4.1 dBTP Range: 9.8 LU

Dynamics Crest factor: 14.2 dB Complexity: 0.81

Stereo Width: 0.58 Correlation: 0.72

Problems MOD Mud buildup 200-400 Hz LOW Sub energy below 30 Hz (rumble)

What to note: Save these numbers (or let your AI assistant remember them). After processing, you’ll compare back to this baseline to verify improvement.

Step 2: EQ with masking data

Why: Instead of sweeping EQ blindly, use masking analysis to know exactly where to cut. You’re making informed surgical decisions, not exploratory ones.

Prompt:

I’m about to EQ the guitars to make room for vocals. Show me exactly where they’re conflicting so I know where to cut

Phantom output:

Masking Analysis: vocals.wav masked by guitar-bus.wav

Overall masking severity: 0.58 (moderate)

Per-octave Overlap: 250 Hz: 0.34 mild 500 Hz: 0.61 significant 1 kHz: 0.72 significant 2 kHz: 0.54 moderate 4 kHz: 0.28 mild

Primary conflict zone: 500 Hz - 2 kHz Recommendation: Cut guitar 2-3 dB at 800 Hz - 1.5 kHz (Q=1.0)

What to do: Apply the suggested EQ cut on the guitar bus, then re-run the analysis:

Prompt (after EQ):

I’ve cut the guitars at 1 kHz. Re-check the masking between vocals and guitars — did it help?

You should see the masking severity drop in the conflict zone. If it’s still above 0.5, you may need a wider cut or a different approach (volume automation, panning separation).

Pro tip

A 2-3 dB cut that’s informed by measurement data is worth more than a 6 dB cut based on guessing. Small, precise moves preserve the tone of both elements while creating separation.

Step 3: Verify dynamics after compression

Why: Compression is the most common source of “my mix lost its punch.” Measuring crest factor before and after tells you objectively how much transient impact you’ve sacrificed.

Prompt:

Compare the dynamics of drums-raw.wav versus drums-compressed.wav — did I kill the transients?

Phantom output:

Dynamics Comparison:

drums-raw.wav: Crest factor: 15.8 dB Dynamic range: 18.2 dB Complexity: 0.74

drums-compressed.wav: Crest factor: 9.2 dB Dynamic range: 11.4 dB Complexity: 0.52

Change: Crest: -6.6 dB (significant transient reduction) Range: -6.8 dB Assessment: Heavy compression applied. Transient character significantly altered. Consider parallel compression or lighter ratio to preserve more punch.

Decision point: A crest factor drop of 3-4 dB is typical for moderate compression. A drop of 6+ dB means you’ve significantly changed the character. Decide if that’s what you wanted.

Step 4: Check stereo image and phase

Why: After panning, stereo effects, and bus processing, verify that your mix translates to mono and doesn’t have unexpected imbalances.

Prompt:

Check the stereo image of my mix bus — is it balanced and mono-compatible?

Phantom output:

Stereo Analysis: mix-v2.wav Width: 0.74 Balance: -0.06 (very slightly left-heavy) Mid/Side: 58% / 42% Correlation: 0.56

Phase Analysis: Overall coherence: 0.71 Per-band: Sub: 0.96 (solid) Low: 0.88 (good) Mid: 0.68 (moderate) High: 0.48 (wide but risky)

Note: High-frequency coherence below 0.5 may cause brightness loss in mono playback.

What to look for:

  • Balance should be within +/- 0.05 of center. A -0.06 left lean is borderline — investigate
  • Correlation below 0.5 in any band means mono cancellation risk
  • High-frequency coherence at 0.48 suggests stereo widening effects may be too aggressive

Pro tip

If high-frequency coherence is below 0.5 and you’re using stereo widening, try reducing the width effect above 8 kHz. Most stereo enhancement works best in the mid-range (1-8 kHz) where it creates space without risking mono collapse.

Step 5: Compare mix versions

Why: After a mixing session, compare your processed mix against the unprocessed baseline from Step 1. Objective data shows what improved and what might have gotten worse.

Prompt:

Compare mix-v2-processed.wav against my baseline mix-v1-unprocessed.wav — what improved and what got worse?

Your AI assistant will compare the measurements and identify:

  • Did the mud problem from the baseline get resolved?
  • Did loudness/dynamics change appropriately?
  • Is the stereo image better defined?
  • Were any new problems introduced?

Quick Reference

  1. Run a full diagnostic on [mix bus] — I want a baseline
  2. Show me where [element A] and [element B] are conflicting
  3. Compare dynamics of [raw] vs [processed] — did I overdo it?
  4. Check the stereo image of my mix bus — is it balanced and mono-compatible?
  5. Compare [new version] against [baseline] — what improved?

Next Steps