38 citations · 77 across the 7 of their papers we have counts for
5 papers · 1 filter
Conditional Generation and Snapshot Learning in Neural Dialogue Systems
Tsung-Hsien Wen, Milica Gasic, Nikola Mrksic +5
Recently a variety of LSTM-based conditional language models (LM) have been applied across a range of language generation tasks. In this work we study various model architectures a…
Continuously Learning Neural Dialogue Management
Pei-Hao Su, Milica Gasic, Nikola Mrksic +5
We describe a two-step approach for dialogue management in task-oriented spoken dialogue systems. A unified neural network framework is proposed to enable the system to first learn…
On-line Active Reward Learning for Policy Optimisation in Spoken Dialogue Systems
Pei-Hao Su, Milica Gasic, Nikola Mrksic +5
The ability to compute an accurate reward function is essential for optimising a dialogue policy via reinforcement learning. In real-world applications, using explicit user feedbac…
Multi-domain Neural Network Language Generation for Spoken Dialogue Systems
Tsung-Hsien Wen, Milica Gasic, Nikola Mrksic +4
Moving from limited-domain natural language generation (NLG) to open domain is difficult because the number of semantic input combinations grows exponentially with the number of do…
Counter-fitting Word Vectors to Linguistic Constraints
Nikola Mrkšić, Diarmuid Ó Séaghdha, Blaise Thomson +6
In this work, we present a novel counter-fitting method which injects antonymy and synonymy constraints into vector space representations in order to improve the vectors' capabilit…