Voice bot with Splunk

I got the opportunity to work with Splunk and Elastic Search for NLP projects.

Requirement:

We have to track the user utterance and responses by Splunk. In my Flask API , have used RASA for a portion of NLU tasks.

Question-Answering system with cdQA-suite

This is Transfer Learning era on NLP tasks.
Have been working on how to use my data set on XLNet and BERT.
Found excellent references with community help

https://towardsdatascience.com/how-to-create-your-own-question-answering-system-easily-with-python-2ef8abc8eb5
https://github.com/cdqa-suite/cdQA

XLNet - A SOTA model

While working on the Q&A system, have found pretrained model on NLP. XLNET is state of the art model for Q&A applications.
XLNet is the combination of Autoregressive  and autoencoding

Generalized Autoregressive Pretraining for Language Understanding.

Generalized -- Pretrain without data correption( masking) by using permutation LM.

Auto regressive – Autoregressive language model but also utilizes bidirectional context

This is better than BERT

References:
https://arxiv.org/abs/1906.08237
https://mlexplained.com/2019/06/30/paper-dissected-xlnet-generalized-autoregressive-pretraining-for-language-understanding-explained/