55 citations · 151 across the 25 of their papers we have counts for
7 papers · 1 filter
Variational Cross-domain Natural Language Generation for Spoken Dialogue Systems
Bo-Hsiang Tseng, Florian Kreyssig, Pawel Budzianowski +4
Cross-domain natural language generation (NLG) is still a difficult task within spoken dialogue modelling. Given a semantic representation provided by the dialogue manager, the lan…
MultiWOZ -- A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling
Paweł Budzianowski, Tsung-Hsien Wen, Bo-Hsiang Tseng +4
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 funda…
Large-Scale Multi-Domain Belief Tracking with Knowledge Sharing
Osman Ramadan, Paweł Budzianowski, Milica Gašić
Robust dialogue belief tracking is a key component in maintaining good quality dialogue systems. The tasks that dialogue systems are trying to solve are becoming increasingly compl…
Nearly Zero-Shot Learning for Semantic Decoding in Spoken Dialogue Systems
Lina M. Rojas-Barahona, Stefan Ultes, Pawel Budzianowski +4
This paper presents two ways of dealing with scarce data in semantic decoding using N-Best speech recognition hypotheses. First, we learn features by using a deep learning architec…
Neural User Simulation for Corpus-based Policy Optimisation for Spoken Dialogue Systems
Florian Kreyssig, Inigo Casanueva, Pawel Budzianowski +1
User Simulators are one of the major tools that enable offline training of task-oriented dialogue systems. For this task the Agenda-Based User Simulator (ABUS) is often used. The A…
Feudal Reinforcement Learning for Dialogue Management in Large Domains
Iñigo Casanueva, Paweł Budzianowski, Pei-Hao Su +4
Reinforcement learning (RL) is a promising approach to solve dialogue policy optimisation. Traditional RL algorithms, however, fail to scale to large domains due to the curse of di…
Sample Efficient Deep Reinforcement Learning for Dialogue Systems with Large Action Spaces
Gellért Weisz, Paweł Budzianowski, Pei-Hao Su +1
In spoken dialogue systems, we aim to deploy artificial intelligence to build automated dialogue agents that can converse with humans. A part of this effort is the policy optimisat…