Automatic Generation of Conversational Skills from Dialog Datasets

Abstract

Modern dialog agents are complex modular systems which, among others, may contain several natural language generation systems named skills. Having enough functionality to be independent chatbots, they often become building blocks for more complex systems able to converse on a range of topics. Such multiskill dialog agents are the closest thing to fully functional open-domain conversational systems. This work proposes an approach to generate conversational skills that, using open-source dialog data and a context of several utterances, can generalize to new domains and generate responses in a controlled and interpretable way. Although it is designed for the open domain, it may be used for automatic skill generation if a more domain-specific dialog skill is required.