/ / project

Machine Translation App

A bilingual translation project focused on Hindi-English and English-Hindi text conversion using fine-tuned machine translation models and a user-friendly application layer.

Focus NLP • Translation • fine-tuning

Tools Opus-MT • Hugging Face • Python

Repo View on GitHub

01 / problem

Improving bilingual translation quality

The core goal of this project was to improve Hindi-English and English-Hindi translation performance using fine-tuned neural machine translation models. Generic multilingual models can be useful, but targeted tuning helps make them more reliable for specific language pairs and real-world use cases.

Once the model quality improved, the next step was packaging the result into an end-user translation application.

02 / approach

Fine-tuning + productization

Fine-tuned Helsinki-NLP Opus-MT models for both Hindi → English and English → Hindi directions
Worked on translation quality improvements through model adaptation and experimentation
Built an app layer to make bilingual translation accessible and usable
Focused on practical output quality rather than only research-level experimentation

03 / what this shows

Strong applied NLP workflow

This project is a good example of the full NLP development loop: model selection, fine-tuning, evaluation, and then turning the result into an accessible application. It combines technical depth with real user value.

04 / impact

Better multilingual communication

The project highlights how machine translation can support broader communication needs, especially when users need a practical bilingual tool rather than a research-only prototype.

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