This repository was archived by the owner on Dec 29, 2022. It is now read-only.
This repository was archived by the owner on Dec 29, 2022. It is now read-only.
How to build a character based seq2seq tensorflow model for spell correction? #366
Description
I am trying to build a character based seq2seq model using tensorflow for food item names correction. The input/output would be like
IN: Cheessseee Quisadillas
OUT: Cheese Quesadillas
I have tried training a word level seq2seq but it does not give much good results. I have also read that we only used attention mechanism on long sequences and I have a Maximum of 6 word sentence(Item Name).
Apart from this, Can I use a language model like BERT or GPT for such task
Can anyone please suggest the changes or provide better resources for implementing the same.?