imosudi/English-Hausa-Language-Translation-Chatbot-using-NLP

To simulate intelligent language translation by training a chatbot to convert English to Hausa using NLP and bilingual datasets. # English–Hausa Language Translation Chatbot using NLP ## Objective To simulate intelligent language translation by training a chatbot to convert English to Hausa using NLP and bilingual datasets. ## Simulation Type Agent-Based / Data-Driven Simulation ## Types of Dataset 1. Parallel corpora (English ↔ Hausa) 2. sentence structures 3. grammar rules ## Possible Sources for Dataset 1. JW300 Dataset 2. OPUS Project 3. WMT 4. AI4D 5. Masakhane ## Dataset URLs 1. opus.nlpl.eu github.com ## Setup Instructions 1. 1. Install Python with NLTK, Hugging Face Transformers, Flask. 2. 2. Preprocess corpus into training-ready format (tokenisation, padding). 3. 3. Setup model architecture or fine-tune existing transformer (e.g. MarianMT). 4. 4. Deploy basic chatbot logic on Flask. ## Implementation Guide 1. 1. Load parallel corpora and train/fine-tune translation model using MarianMT or Transformer. 2. 2. Define chatbot agent with NLP pipeline: input tokenisation → translation → response generation. 3. 3. Simulate user sessions and model translation accuracy or confidence scores. 4. 4. Evaluate BLEU scores, latency, and fluency. ## Expected Output(s) 1. "- Real-time English to Hausa translation 2. - Prediction of optimal responses 3. - BLEU score visualisations 4. - Chatbot latency and performance charts 5. - Confusion matrix for translation errors" ## Background Studies ### Natural Language Processing (NLP) ### Neural Machine Translation (NMT) ### Sequence-to-Sequence Modelling ### Hausa Language Morphology and Syntax ### Evaluation Metrics for Translation Accuracy