Testing AIVA and Suno: Bridging the Gap Between Sound and Emotion

Hands-on evaluation of AIVA and Suno using my own music: I created a David Bowie-inspired ambient composition in AIVA (parametric/symbolic generation) and a Norah Jones reinterpretation of my original song in Suno (text-to-audio synthesis), then used Moises for stem separation and iZotope Ozone for AI mastering to prep a studio demo. Both generation tools excel at ideation but fail at expressive nuance, revealing the semantic gap between surface-level sound and genuine musical meaning. The process exposed how dataset bias kills timbral depth and emotional realism. This analysis bridges technical concepts (MIR, spectral masking, latent representations) with practical workflow decisions: identifying where AI tools genuinely enhance production.

Phil Conil - Berklee College of Music

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