دراسة فالإيقاع المحسوس (Lilat al-Ihsas)
AI Process/Open Source Software: HUMAN, Google Flow Music (Lyria 3.5), Claude.ai, ChatGPT, Perchance.org – DAW: Audacity 4 (alpha), OS: Linux (Ubuntu 26.04)
Lila (or Derdeba), the name for a traditional Gnawa night-long trance ceremony, signals that the listener is engaging with the tradition specifically, not just borrowing its aesthetics.
What’s actually in the signal
Since Google Flow responds to descriptive/sensory language rather than technical parameters (Hz values, dB, ms attack times won’t mean much to it), I translated each suggestion into the kind of phrasing it can actually act on, matching the style of the original prompts:
Primary prompt:
“Deep sub-bass rumble with pulsing double-tone beating, heavy tactile 808 hits with sharp punchy attacks, layered over slow rolling low-end sustain, rhythmic pressure waves you feel move from chest to skin, physical depth, no treble, no melody, weighted and percussive, dynamic contrast between hard transient hits and soft rumbling beds. Moroccan Gnawa-inspired hypnotic groove, guembri-style bass ostinato reimagined as sub-bass pulse, qraqeb castanet-like rhythmic clicks felt as sharp transients, trance-inducing repetitive polyrhythm, 6/8 and 12/8 rhythmic feel, Amazigh/Berber percussion patterns, call-and-response rhythmic phrasing, ceremonial and hypnotic, physical trance rhythm”
What each piece maps to:
What the additions map to:
One thing that was worth testing: text-to-music models sometimes default to surface-level “exotic” tropes (ornamental melody, specific instrument timbres) rather than rhythmic structure when they see a cultural tag like “Moroccan.” Since the whole concept is bass/rhythm-only with treble stripped out, I needed to reinforce “no melody, no treble” again, “negative prompts,” near the cultural descriptors specifically, as the AI model/instance at times may try to sneak in a flute or vocal line to signal “Moroccan-ness” tonally instead of rhythmically.
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