Adapting a conversational text generator for online chatbot messaging

Abstract

Conversational interfaces and chatbots have a long history, but have only recently been hyped as a disruptive technology ready to replace mobile apps and Web sites. Many online messaging platforms have introduced support to third-party chatbots, which can be procedurally programmed, but usually rely on a retrieval-based specification language (such as AIML), natural language processing to detect the user’s intent, or on machine learning. In this work we present a work-in-progress integration of a widely-used system for story generation, the Tracery grammar, a conversational agent design tool, the Bottery system, and online messaging platforms. The proposed system provides a complete and easy-to-use system that allows the creation of chatbots with a graph-based dialogue structure, a contextual memory, pattern-based text matching, and advanced text generation capabilities, that aims for being well-suited for experts and technically unskilled authors alike. Features of the system and future additions are discussed and compared to existing solutions.