In this paper, we present our Alexa Prize Grand Challenge 4 socialbot: Proto. Leveraging diverse sources of world knowledge, and powered by a suite of neural and rule-based natural language understanding modules, state-of-the-art neural generators, novel state-based deterministic generators, an ensemble of neural re-rankers, a robust post-processing algorithm, and an efficient overall conversation strategy, Proto strives to be able to converse coherently about a diverse range of topics of interest to humans, and provide a memorable experience to the user. In this paper we dissect and analyze the different components and conversation strategies implemented by our socialbot, which enables us to generate colloquial, empathetic, engaging, self-rectifying, factually correct, and on-topic response, which has helped us achieve consistent scores throughout the competition.
@article{arxiv.2109.02513,
title = {Proto: A Neural Cocktail for Generating Appealing Conversations},
author = {Sougata Saha and Souvik Das and Elizabeth Soper and Erin Pacquetet and Rohini K. Srihari},
journal= {arXiv preprint arXiv:2109.02513},
year = {2021}
}