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@@ -39,3 +39,10 @@ The project now features a high-performance, Apple Silicon-optimized pipeline th
 2. Transcribes using **MLX-Whisper (small.en)**.
 3. Translates using **MarianMT (EN-ES)**.
 4. Operates entirely locally with hardware acceleration.
+
+## Phase 5: Simultaneous Multi-Language Translation
+- **Goal:** Provide translations in Spanish, French, and Arabic at the same time.
+- **Approach:** 
+    - Refactored the script to support a dictionary of multiple `MarianMT` models.
+    - Each transcribed English segment is passed through each loaded translation engine sequentially.
+- **Performance on M2:** Loading 3-4 specialized models + Whisper is highly efficient, using ~1.5GB of RAM and providing near-instant results.