Gbẹdu
Gbẹdu (pronounced geh-doo — Yoruba for “groove”) is a Datacraft Labs experiment in automated African music production. Feed it a genre, mood, language, and target BPM — it outputs a complete track with vocals, instrumentation, and lyrics in under 2 minutes.
Key Features
From genre prompt to chart-ready master — the full African music production pipeline, automated end-to-end.
Full Track in 2 Minutes
From a simple prompt to a complete Afrobeats track — vocals, drums, bass, lead melody, and harmony — in under 120 seconds. The generation pipeline runs on 4× A100s. Tracks are indistinguishable from human production in blind ABX tests with 200-person panels.
8+ African Language Lyrics
Lyric generation trained on 50,000 Afrobeats, Afropop, and Amapiano songs spanning Yoruba, Igbo, Hausa, Swahili, Lingala, Wolof, Twi, and Zulu. The LLM fine-tune handles code-switching — the way African artists naturally mix languages mid-track.
RVC v2 Voice Cloning
Retrieval-based Voice Conversion v2 creates a vocal character consistent across tracks within a project. The generated voice has timbre, vibrato, and phrasing consistent with the target style. Not a real person’s voice — synthesized from a style spec.
ACE-Step 1.5 Music Model
ACE-Step is a diffusion-based music generation model fine-tuned on African rhythmic patterns — 12/8 time signatures, polyrhythmic percussion, talking drum patterns. Captures the swing and groove that generic Western music models miss.
Automated Mix & Master
Matchering-based loudness normalization to streaming platform targets (Spotify −14 LUFS, Apple −16 LUFS). EQ curves matched to reference tracks by genre. Auto-sidechain compression for the kick-bass relationship. Output: FLAC master + MP3 streaming version.
Chart Prediction Score
A fine-tuned classifier predicts streaming chart potential by region (Nigeria, Kenya, Ghana, South Africa) based on hook memorability, energy profile, and lyric sentiment. Iterative generation keeps running until the target score is hit.
Automating chart-beating Afrobeats. Just because we can.
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