Open AccessConversational Chatbot with Attention Model
Author(s) -
P. Srikanth,
Ushitaasree,
G. Paavai Anand
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.b6316.129219
Subject(s) - chatbot , computer science , perplexity , language model , artificial intelligence , natural language processing , sentence , conversation , transformer , natural language understanding , speech recognition , softmax function , natural language , deep learning , engineering , linguistics , philosophy , voltage , electrical engineering
A Chatbot is an Artificial Intelligence (AI) software that can give a simulation of a conversation between two humans. This Chatbot is based on State of the Art Transformer model architecture which works on Attention mechanism. The transformer model is a very efficient Sequence to Sequence model. Machine translation is at its core , simply a task in which you map the sentence to another sentence. Sentences consist of words that are equivalent to mapping to a different sequence. Beam search and Byte-pair encoding are the algorithms used in our model for heuristic searching in decoder units. A combination of many Unsupervised prediction tasks were carried out by fine-tuning using a multi-task objective every time the user starts the conversation. It takes a new persona for every new session opened and communicates with that persona which is chosen at random. Forwarding the perplexity by the ability to understand and generate natural language this model gives a whooping Hits@1 score efficiency as high as 80.9 percentage.