Dialogue Management

18 papers with code • 0 benchmarks • 1 datasets

( Image credit: Bocklisch et al. )


Most implemented papers

Rethinking Action Spaces for Reinforcement Learning in End-to-end Dialog Agents with Latent Variable Models

snakeztc/NeuralDialog-LaRL NAACL 2019

Defining action spaces for conversational agents and optimizing their decision-making process with reinforcement learning is an enduring challenge.

End-to-end optimization of goal-driven and visually grounded dialogue systems

GuessWhatGame/guesswhat 15 Mar 2017

End-to-end design of dialogue systems has recently become a popular research topic thanks to powerful tools such as encoder-decoder architectures for sequence-to-sequence learning.

Conversation Graph: Data Augmentation, Training and Evaluation for Non-Deterministic Dialogue Management

huawei-noah/noah-research 29 Oct 2020

We propose the Conversation Graph (ConvGraph), a graph-based representation of dialogues that can be exploited for data augmentation, multi-reference training and evaluation of non-deterministic agents.

Strategic Dialogue Management via Deep Reinforcement Learning

cuayahuitl/SimpleDS 25 Nov 2015

This paper describes a successful application of Deep Reinforcement Learning (DRL) for training intelligent agents with strategic conversational skills, in a situated dialogue setting.

Rasa: Open Source Language Understanding and Dialogue Management

RasaHQ/rasa 14 Dec 2017

We introduce a pair of tools, Rasa NLU and Rasa Core, which are open source python libraries for building conversational software.

Towards Learning Transferable Conversational Skills using Multi-dimensional Dialogue Modelling

skeizer/madrigal 31 Mar 2018

Recent statistical approaches have improved the robustness and scalability of spoken dialogue systems.

An Ontology-Based Dialogue Management System for Banking and Finance Dialogue Systems

TimKettenacker/puffin 13 Apr 2018

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.

Fully Statistical Neural Belief Tracking

nmrksic/neural-belief-tracker ACL 2018

This paper proposes an improvement to the existing data-driven Neural Belief Tracking (NBT) framework for Dialogue State Tracking (DST).

MultiWOZ - A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling

budzianowski/multiwoz EMNLP 2018

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.