Designing NLP solutions for an underrepresented language: Moroccan Darija, focusing on idioms and sarcasm
# NLP for Moroccan Darija — Tackling Low-Resource Machine Translation
Salam, merhaba! 👋 Welcome to **NLP-Darija** , a project where I explore, analyze, and challenge the boundaries of current Natural Language Processing (NLP) techniques by focusing on **Moroccan Darija**, a rich yet low-resource language.
---
## Project Overview
In this project, I investigate the **capabilities and limitations of Large Language Models (LLMs)** — including **GPT-4** and **Claude** — for **Moroccan Darija to English Machine Translation**. My evaluation spans:
- **Sentence-level translation**
- **Idiomatic and sarcastic expressions**
- **POS tagging and dependency parsing**
- **Code-switched text analysis (Darija, French, Arabic, Arabizi)**
This repository serves as a **call to action** in the NLP community, exposing the critical gaps in support for **non-standardized and underrepresented languages**. Moroccan Darija is particularly challenging due to its:
- Non-standardized orthography (including Arabizi)
- Morphological complexity
- Heavy linguistic borrowing from **Amazigh**, **French**, and **Modern Standard Arabic**
- Frequent **code-switching**
- Unique **phonetic substitutions using numbers** (e.g., 7 = ح)
---
## What I Did
### Tools & Techniques
- Syntax parsing with LLMs for **POS tagging** and **dependency parsing**
- Prompt engineering with **OpenAI GPT-4** and **Anthropic Claude**
- Evaluation via **human assessments** + **automatic metrics**
- Linguistic analysis of **idioms**, **sarcasm**, and **phonetic variation**
### Evaluation
- Compared LLM translations to human-annotated reference sets
- Highlighted failure points on idiomatic expressions and sarcasm
- Demonstrated how **prompt design** directly impacts translation quality
- Assessed how **LLMs handle Arabizi and code-switching**
---
## Key Insights
- **Translation quality improves with task-specific prompt tuning**
- No robust open-source **Darija-English parallel corpus** exists
- There is an ur …