This project is an implementation of an Encoder-Decoder architecture for English to Hindi translation using Neural Networks. The implementation is done using Keras, TensorFlow, NumPy, and Pandas.
The Encoder-Decoder architecture is a popular technique for sequence-to-sequence learning. In this project, we have used a recurrent neural network (RNN) and LSTM as the encoder and decoder.
The training data for the model is a dataset of English sentences and their corresponding Hindi translations. The model is trained on this data to learn the mapping between the two languages.
The final validation accuracy of the model is around 74 percent.
To run this project, you will need the following software:
- Python 3.6 or later
- TensorFlow 2.0 or later
- Keras
- NumPy
- Pandas
Here are some examples of English sentences and their corresponding Hindi translations:
| English | Hindi |
|---|---|
| how long have you been abroad | आप विदेश में कबसे हैं |
| will you sing me a beatles song | तुम मेरे लिए एक बीटल्स का गाना गा सकते हो क्या |