Tartan: A retrieval-based socialbot powered by a dynamic finite-state machine architecture

December 04, 2018 ยท Declared Dead ยท ๐Ÿ› arXiv.org

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Authors George Larionov, Zachary Kaden, Hima Varsha Dureddy, Gabriel Bayomi T. Kalejaiye, Mihir Kale, Srividya Pranavi Potharaju, Ankit Parag Shah, Alexander I Rudnicky arXiv ID 1812.01260 Category cs.CL: Computation & Language Cross-listed cs.AI Citations 17 Venue arXiv.org Last Checked 4 months ago
Abstract
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.
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