Rofeeah-Tijani/-Yoruba-English-Sequence-to-Sequence-Translation-Model
Domain:
natural language processingRecord type:
model
Creator:
Rof
Host:
# 🌍 Yoruba → English Sequence-to-Sequence Translation Model
This project demonstrates a **Sequence-to-Sequence (Seq2Seq) neural network** for translating Yoruba sentences into English using deep learning.
It was built to understand how encoder-decoder architectures work using GRU-based recurrent neural networks.
---
# 🧠 What is this project about?
This project builds a model that learns:
> Yoruba sentence → English sentence
Instead of memorizing translations, the model learns patterns between languages using a neural network.
---
# ⚙️ How it works (High-Level)
The model follows the Seq2Seq architecture:
Input Sentence (Yoruba)
↓
Encoder (GRU)
↓
Context Vector (compressed meaning)
↓
Decoder (GRU)
↓
Output Sentence (English)
---
# 🧩 Key Concepts Used
## 1. Sequence-to-Sequence (Seq2Seq)
A model that converts one sequence into another sequence.
Examples:
- Yoruba → English translation
- Text summarization
- Chatbots
---
## 2. Encoder-Decoder Architecture
- **Encoder**: Reads and understands the input sentence
- **Decoder**: Generates the output sentence step-by-step
---
## 3. GRU (Gated Recurrent Unit)
A type of recurrent neural network that helps the model remember important information in sequences.
Used in both encoder and decoder.
---
## 4. Embedding Layer
Converts words into dense numerical vectors so the model can understand meaning.
---
## 5. Teacher Forcing (Training Concept)
During training, the correct previous word is used to improve learning stability.
---
# 🧪 Dataset
A small custom dataset of Yoruba-English sentence pairs:
Example:
| Yoruba | English |
|--------|--------|
| mo n lo si ile | i am going home |
| inu mi dun | i am happy |
| o n jeun | he is eating |
---
# 🏗️ Model Architecture
```
Encoder:
Embedding → GRU → Context Vector
Decoder:
Embedding → GRU → Dense (Softmax)
```
---
# 📦 Requirements
```bash
tensorflow
numpy
```
---
# 🚀 How to run
```bash
# Clone the repository
git clone github.com …
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