Umbaji/NMTMD

Official repository for the Opensource Textdataset for NMT for local langues in West Africa (EWE Corpus) # NMTMD (NMT-Melinda-Dataset) Official repository for the Opensource Text dataset for NMT for local languages in West Africa (EWE Corpus) and implement the Yodi model afterward. Note: This repository will evolve into the official repository for the Yodi model, once the necessary data is gathered. # Objective ##### • Develop a Machine Translation Text and Speech Dataset NMT for local languages in West Africa (EWE Corpus) # Key Results ###### -> Develop & Measure the accuracy or the performance of the Yodi model from this dataset for text-to-text translation. ###### -> Develop & Measure the accuracy of Yodi built from this dataset for Speech recognition. ##### Remark: Getting accurate data and labeled data from available sources online or in local written papers would be necessary for machine sentence translation. ## Using the Updated Dictionaries We have transformed and analyzed two Ewe-English dictionaries: KABDICT525 and EWEDICT995. These dictionaries are now available as Python modules for easy integration into your projects. ### Accessing the Dictionaries 1. The transformed dictionaries are located in the `Dictionaries` folder: - `Dictionaries/kabdict525.json` - `Dictionaries/ewedict995.json` 2. To use these dictionaries in your Python scripts, you can import them as follows: ```python import json # Load KABDICT525 with open('Dictionaries/kabdict525.json', 'r', encoding='utf-8') as f: kabdict = json.load(f) # Load EWEDICT995 with open('Dictionaries/ewedict995.json', 'r', encoding='utf-8') as f: ewedict = json.load(f) # Example usage print(kabdict.get('word', 'Word not found')) print(ewedict.get('word', 'Word not found')) ``` # Ongoing Feel free to share your analytics in the discussions! Instructions are available in project_contributions_instructions.txt Please register at sites.google.com to build the largest NMT text Dataset for West Africa.