Seq2Seq AI Chatbot with Attention Mechanism

TL;DR

This paper discusses the development of an AI chatbot using sequence-to-sequence models with attention mechanisms, highlighting recent advances in neural network-based conversational agents.

Contribution

It introduces a Seq2Seq model with attention for improved chatbot performance, emphasizing end-to-end training in NLP applications.

Findings

Enhanced conversational coherence with attention mechanisms

Improved response relevance over baseline models

Demonstrated effectiveness of neural networks in chatbots

Abstract

Intelligent Conversational Agent development using Artificial Intelligence or Machine Learning technique is an interesting problem in the field of Natural Language Processing. With the rise of deep learning, these models were quickly replaced by end to end trainable neural networks.