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Found 15 papers, 3 papers with code
ConvLab-3: A Flexible Dialogue System Toolkit Based on a Unified Data Format
To address this issue, we present ConvLab-3, a flexible dialogue system toolkit based on a unified TOD data format.
Dialogue Evaluation with Offline Reinforcement Learning
They are ideally evaluated with human users, which however is unattainable to do at every iteration of the development phase.
GenTUS: Simulating User Behaviour and Language in Task-oriented Dialogues with Generative Transformers
In addition, its behaviour can be further shaped with reinforcement learning opening the door to training specialised user simulators.
Dynamic Dialogue Policy for Continual Reinforcement Learning
The lack of a framework with training protocols, baseline models and suitable metrics, has so far hindered research in this direction.
Robust Dialogue State Tracking with Weak Supervision and Sparse Data
Our architecture and training strategies improve robustness towards sample sparsity, new concepts and topics, leading to state-of-the-art performance on a range of benchmarks.
What Does The User Want? Information Gain for Hierarchical Dialogue Policy Optimisation
The dialogue management component of a task-oriented dialogue system is typically optimised via reinforcement learning (RL).
EmoWOZ: A Large-Scale Corpus and Labelling Scheme for Emotion Recognition in Task-Oriented Dialogue Systems
We report a set of experimental results to show the usability of this corpus for emotion recognition and state tracking in task-oriented dialogues.
Ranked #1 on
Emotion Recognition in Conversation
on EmoWoz
Emotion Recognition in Conversation
Task-Oriented Dialogue Systems
Uncertainty Measures in Neural Belief Tracking and the Effects on Dialogue Policy Performance
This highlights the importance of developing neural dialogue belief trackers that take uncertainty into account.
Domain-independent User Simulation with Transformers for Task-oriented Dialogue Systems
TUS can compete with rule-based user simulators on pre-defined domains and is able to generalise to unseen domains in a zero-shot fashion.
Out-of-Task Training for Dialog State Tracking Models
Dialog state tracking (DST) suffers from severe data sparsity.
LAVA: Latent Action Spaces via Variational Auto-encoding for Dialogue Policy Optimization
In this paper, we explore three ways of leveraging an auxiliary task to shape the latent variable distribution: via pre-training, to obtain an informed prior, and via multitask learning.
Knowing What You Know: Calibrating Dialogue Belief State Distributions via Ensembles
The ability to accurately track what happens during a conversation is essential for the performance of a dialogue system.
TripPy: A Triple Copy Strategy for Value Independent Neural Dialog State Tracking
In this paper we present a new approach to DST which makes use of various copy mechanisms to fill slots with values.
Ranked #11 on
Multi-domain Dialogue State Tracking
on MULTIWOZ 2.1
dialog state tracking
Multi-domain Dialogue State Tracking
+2
Unsupervised Counselor Dialogue Clustering for Positive Emotion Elicitation in Neural Dialogue System
Positive emotion elicitation seeks to improve user{'}s emotional state through dialogue system interaction, where a chat-based scenario is layered with an implicit goal to address user{'}s emotional needs.
Construction of Japanese Audio-Visual Emotion Database and Its Application in Emotion Recognition
Emotional aspects play a vital role in making human communication a rich and dynamic experience.
