🎙 LEHJA — build status
Updated 2026-06-13 15:15:01 UTC · auto-refresh 60s · cron every 5 min
OVERALL (Arabic track + MT): 50%
H100 NVL: 85% GPU · active jobs 10 · VRAM 45.1 GB used / 48.0 GB free of 93.6 GB
🔥 TRAINING LIVE — model is learning diacritized Quranic recitation (GPU-heavy phase).
📋 Tasks — main & sub
✅ ✦. Urdu voice model (previous milestone) 100% ✅ CosyVoice2 Urdu LoRA trained + delivered · validation PASS · median CER 0.065 · model on app-server
✅ 1. Build Quranic-Arabic pipeline (canonical alignment, full tashkeel) 100% ✅ Diacritic-preserving aligner + mining/prep/train/validate scripts
✅ 2. Canonical Uthmani Quran text + alignment index 100% ✅ 6236 ayahs, full Uthmani Hafs (zabar/zer/pesh/shadda/tanwin/ghunna)
✅ Skeleton search index — rough transcript → exact ayah span
✅ 3. Mine in-domain Arabic recitation (your QTM corpus) 100% ✅ whisper-ar VAD-segment + inline Quran align · 11,900/12,000 files · 8/8 shards done
✅ clean recitation clips harvested · 11,237 clips · 1223.6 min · 3,041 distinct ayahs
✅ 4. Canonical-align → diacritized labels + confidence gate 100% ✅ perfect diacritized labels (alignment inline per clip)
✅ high-confidence gate (match≥85) + dedup · 7,238 train-grade clips
⬜ 5. Train + validate + package Quranic Arabic LoRA 0% 🔄 CosyVoice2 fine-tune (learn diacritized recitation) · 25 epochs planned
⬜ validate: recites correct Arabic? (whisper-readback)
⬜ package CosyVoice2-0.5B-ar + download to app-server
⬜ MT. Flagship MT benchmark (Qwen3.6-35B-A3B vs Qwen3-14B) 0% ⬜ models downloaded (Qwen3-14B + Qwen3.6-35B-A3B) · queued after training
📊 Arabic data harvest
Recitation clips mined: 11,237 · 1223.6 min clean audio
Train-grade (match≥85): 7,238 clips · 3,041 distinct ayahs covered
Source: your QTM Quran-recitation corpus (30,165 Arabic files available)
Approach: every clip's rough transcript is matched to the canonical Uthmani Quran text, so labels carry perfect diacritics (zabar/zer/pesh/tashdeed/tanwin/ghunna) — and non-recitation (Urdu explanation, repetition) is auto-filtered.