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Urdu_to_Roman_Urdu_Transliterator

I worked on this project with my colleague Sumair Ijaz Hashmi. This was a course project for a graduate level course on Natural Language Processing at LUMS, Pakistan.

A neural machine translation task executed with a seq2seq bidirectional LSTM Encoder-Decoder Model with Attention implemented in Keras. Using greedy search for sentence prediction resulted in a BLEU score of 74 and a ROGUE score of 0.90 for medium length sentences (10 words < sentence length <=20 words).

We used bucketing in our work for more specialized, better performing models.

NLP_Data.ipynb is data processing and manipulation.

NLP_Bucket_1.ipynb is the model,predictions, and results for sentences of lengths 0 to 10.

NLP_Bucket_2.ipynb is the model,predictions, and results for sentences of lengths 10 to 20.

NLP_Bucket_3.ipynb is the model,predictions, and results for sentences of lengths 20 to 30.

Reference paper and dataset owners: https://sci-hub.se/10.1142/s0218001421520017

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An Urdu to Roman-Urdu Transliterator

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