Dialogue Management
24 papers with code • 0 benchmarks • 1 datasets
( Image credit: Bocklisch et al. )
Benchmarks
These leaderboards are used to track progress in Dialogue Management
Latest papers
Emora STDM: A Versatile Framework for Innovative Dialogue System Development
This demo paper presents Emora STDM (State Transition Dialogue Manager), a dialogue system development framework that provides novel workflows for rapid prototyping of chat-based dialogue managers as well as collaborative development of complex interactions.
Cascaded LSTMs based Deep Reinforcement Learning for Goal-driven Dialogue
Dialogue embeddings are learned by a LSTM at the middle of the network, and updated by the feeding of all turn embeddings.
Modeling Multi-Action Policy for Task-Oriented Dialogues
Dialogue management (DM) plays a key role in the quality of the interaction with the user in a task-oriented dialogue system.
Are You for Real? Detecting Identity Fraud via Dialogue Interactions
In this paper, we focus on identity fraud detection in loan applications and propose to solve this problem with a novel interactive dialogue system which consists of two modules.
Rethinking Action Spaces for Reinforcement Learning in End-to-end Dialog Agents with Latent Variable Models
Defining action spaces for conversational agents and optimizing their decision-making process with reinforcement learning is an enduring challenge.
End-to-End Knowledge-Routed Relational Dialogue System for Automatic Diagnosis
Besides the challenges for conversational dialogue systems (e. g. topic transition coherency and question understanding), automatic medical diagnosis further poses more critical requirements for the dialogue rationality in the context of medical knowledge and symptom-disease relations.
MultiWOZ - A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling
Even though machine learning has become the major scene in dialogue research community, the real breakthrough has been blocked by the scale of data available. To address this fundamental obstacle, we introduce the Multi-Domain Wizard-of-Oz dataset (MultiWOZ), a fully-labeled collection of human-human written conversations spanning over multiple domains and topics. At a size of 10k dialogues, it is at least one order of magnitude larger than all previous annotated task-oriented corpora. The contribution of this work apart from the open-sourced dataset is two-fold:firstly, a detailed description of the data collection procedure along with a summary of data structure and analysis is provided.
Fully Statistical Neural Belief Tracking
This paper proposes an improvement to the existing data-driven Neural Belief Tracking (NBT) framework for Dialogue State Tracking (DST).
An Ontology-Based Dialogue Management System for Banking and Finance Dialogue Systems
We introduce an ontology-based dialogue manage(OntoDM), a dialogue manager that keeps the state of the conversation, provides a basis for anaphora resolution and drives the conversation via domain ontologies.
Towards Learning Transferable Conversational Skills using Multi-dimensional Dialogue Modelling
Recent statistical approaches have improved the robustness and scalability of spoken dialogue systems.