An Ensemble Dialogue System for Facts-Based Sentence Generation
This addresses the problem of generating fact-based dialogue responses for dialogue systems, but it is incremental as it builds on existing ensemble methods.
The study tackled generating responses based on real-world facts by combining context and external facts, resulting in a system that performed significantly better than individual modules and worked well on the DSTC7-Task2 objective evaluation.
This study aims to generate responses based on real-world facts by conditioning context and external facts extracted from information websites. Our system is an ensemble system that combines three modules: generated-based module, retrieval-based module, and reranking module. Therefore, this system can return diverse and meaningful responses from various perspectives. The experiments and evaluations are conducted with the sentence generation task in Dialog System Technology Challenges 7 (DSTC7-Task2). As a result, the proposed system performed significantly better than sole modules, and worked fine at the DSTC7-Task2, specifically on the objective evaluation.