Logo Lanfrica

AlvinSMoyo/2XYDqXDc6wzA716j

Domaine:

natural language processing

Type de record:

model
Créateur:
Alv
Hôte:
MonReader Cognitive Engine — a multi-modal AI pipeline (CNN • OCR • NLP • TTS) that turns a Shona hymnbook into accessible audio. Colab-first. # MonReader Cognitive Engine: A Multi‑Modal AI Pipeline > **Turn a physical Shona hymnbook into an interactive, accessible, and audible experience.** MonReader is a six‑phase, end‑to‑end AI system spanning **Computer Vision (CNN)**, **OCR**, **NLP**, and **Text‑to‑Speech**. The engine detects page turns, extracts text from images, understands cross‑lingual meaning, and finally **speaks** the content in a custom‑cloned Shona voice. --- ## 🔭 Project Overview The mission was to build a complete pipeline that could: 1. **Visually detect** page turns to trigger a scanner. 2. **Accurately extract** Shona text from scanned images. 3. **Analyze and align** meaning across Shona ⇄ English. 4. **Synthesize** high‑quality audio in a custom‑cloned Shona voice. This was accomplished over six distinct phases, each building upon the last. --- ## 🗺️ The Six Phases of Development ### 📸 Phase 1 — Image Classification Pipeline **Essence:** An end‑to‑end **image classification** project to flawlessly distinguish a page being turned (**flip**) vs held steady (**notflip**)—the trigger for scanning. **Highlights** * **Transfer Learning with CNNs:** A rigorous bake‑off across leading architectures. * **AlvinNet + Lion Optimizer:** A lightweight, custom CNN refined with **Lion**. * **Performance & Explainability:** Near‑perfect **F1 score**; **Grad‑CAM** verified feature focus. --- ### 📖 Phase 2 — From Scanned Page to Digital Text (OCR on the Shona Hymnal) **Essence:** A focused **OCR** challenge on high‑resolution ELCZ Shona hymnbook images. **Highlights** * **Competitive OCR:** **EasyOCR** vs **Tesseract** head‑to‑head. * **Quantitative Evaluation:** Winner selected via **Levenshtein distance**. --- ### 🧠 Phase 3 — Hybrid AI for Hymn Transcription & Analysis **Essence:** Beyond standalone OCR—build a **Hybrid AI Pipeline** comparing **Vision‑Language Models (VLMs)** against a two‑step flow where a **PLM** corrects OCR. **Highlights** * **Modern Model Bake‑Off:* …