Dialogue Management

DialoGLUE is a natural language understanding benchmark for task-oriented dialogue designed to encourage dialogue research in representation-based transfer, domain adaptation, and sample-efficient task learning. It consisting of 7 task-oriented dialogue datasets covering 4 distinct natural language understanding tasks. Source: DialoGLUE: A Natural Language Understanding Benchmark for Task-Oriented Dialogue

The Situated Corpus Of Understanding Transactions (SCOUT) is a multi-modal collection of human-robot dialogue in the task domain of collaborative exploration. The corpus was constructed from multi-phased Wizard-of-Oz experiments where human participants gave verbal instructions to a remotely-located robot to move and gather information about its surroundings. Each dialogue involved a human Commander, a Dialogue Manager (DM), and a Robot Navigator (RN), and took place in physical or simulated environments. SCOUT contains Transcripts of human-robot dialogues, aligned with the Images taken by the robot at the request of the Commander. The transcripts have been annotated with Dialogue Structure, including Transcaction Units (TUs), Antecedents, and Relations. A subset of utterances have been annotated with Dialogue Semantics including Standard-AMR and Dialogue-AMR. A subset of the Maps have been curated that depict the LIDAR Maps at the end of the dialogue and have been annotated as Exploration Maps.