feat: add Motif Storyboard composition plugin
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# Devath reference measurements
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Analyzed the seven user-supplied FLACs in this workspace using their actual audio
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samples. This is signal analysis of the rendered mixes, not a listening-based
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transcription of their melodies or an account of the artist's intent.
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## Observable contrasts
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Approximate reference points from the one-second summaries:
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| Recording | Measured pattern | Useful compositional question |
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|---|---|---|
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| Henka | A marked reduction in level/attacks around 2:03–2:35, followed by a strong return; another reduction near 3:57. | What can be withheld so the recognizable idea matters when it returns? |
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| Phantasy | Lower, interrupted activity around 1:27–2:23, contrasting with the stronger regions before and after. | Can a fragment carry continuity across a less active passage? |
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| Blumengarten | An interrupted middle region around 2:02–3:02, then renewed sustained activity; marked reduction near 4:19. | Can the same identity support different densities and articulations? |
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| quiet wish | A broad reduction around 1:53–2:32 before activity returns. | Does a long breath make the return more effective than adding notes? |
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| Light Aspect | A smaller reduction around 1:33–1:49 and a later reduction around 3:04. | Can a shorter contrast work without rebuilding the entire phrase? |
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| Petals | More consistent relative activity through much of the first four minutes, with short dips and a lower closing region after roughly 4:11. | Can development happen with small changes while the groove stays continuous? |
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| VERDICT. remix | Stronger sustained regions roughly 1:01–1:48 and 3:02–3:48, separated by a less active region. | What should remain recognizable across contrasting presentations? |
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These times are prompts for human listening, not asserted verse/drop boundaries.
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RMS is affected by arrangement and mastering. Spectral attacks include drums and
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sound-design transients, so neither curve measures melodic note density.
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The design inference is to support both subtraction/return and continuous-groove
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writing, rather than force every generated phrase through the same climb and
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resolution. The implementation includes optional fixed groove, fragments, note
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subtraction, different articulations, register return, and section composition.
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This does **not** establish that Devath used those exact note-level operations.
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No source notes or audio were copied into presets or used to train a model.
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## Reproduce
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```sh
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python scripts/analyze-references.py . --output docs/reference-analysis
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```
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Requires `ffmpeg`, NumPy, and Matplotlib. The script decodes mono audio at 11,025
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Hz and uses a 2,048-sample Hann window with a 256-sample hop. It summarizes RMS
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and positive log-spectral flux per second, normalizing each curve to its own
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95th percentile for visibility. Candidate texture changes compare standardized
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low/mid/high-band energy over eight-second neighborhoods, with separated peaks.
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[Raw summaries](reference-analysis/measurements.json) include track durations and
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within-track 80th/20th percentile ratios. Automatic tempo and chord estimates are
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intentionally omitted: coarse onset periodicity and spectral peaks are not
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reliable transcriptions of these full mixes.
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A detailed melodic study still needs a listening pass with annotated motifs,
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harmonic rhythm, bass/lead relationships, and returns, ideally checked against
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stems or MIDI. These measurements alone cannot identify exact chord progressions,
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voice leading, emotional meaning, or which sound carries the melody.
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