This paper describes the Tartan conversational agent built for the 2018 Alexa Prize Competition. Tartan is a non-goal-oriented socialbot focused around providing users with an engaging and fluent casual conversation. Tartan's key features include an emphasis on structured conversation based on flexible finite-state models and an approach focused on understanding and using conversational acts. To provide engaging conversations, Tartan blends script-like yet dynamic responses with data-based generative and retrieval models. Unique to Tartan is that our dialog manager is modeled as a dynamic Finite State Machine. To our knowledge, no other conversational agent implementation has followed this specific structure.
@article{arxiv.1812.01260,
title = {Tartan: A retrieval-based socialbot powered by a dynamic finite-state machine architecture},
author = {George Larionov and Zachary Kaden and Hima Varsha Dureddy and Gabriel Bayomi T. Kalejaiye and Mihir Kale and Srividya Pranavi Potharaju and Ankit Parag Shah and Alexander I Rudnicky},
journal= {arXiv preprint arXiv:1812.01260},
year = {2018}
}