Pomdp-based statistical spoken dialog systems: A review

S Young, M Gašić, B Thomson… - Proceedings of the …, 2013‏ - ieeexplore.ieee.org
Statistical dialog systems (SDSs) are motivated by the need for a data-driven framework that
reduces the cost of laboriously handcrafting complex dialog managers and that provides …

Survey on evaluation methods for dialogue systems

J Deriu, A Rodrigo, A Otegi, G Echegoyen… - Artificial Intelligence …, 2021‏ - Springer
In this paper, we survey the methods and concepts developed for the evaluation of dialogue
systems. Evaluation, in and of itself, is a crucial part during the development process. Often …

A survey of available corpora for building data-driven dialogue systems

IV Serban, R Lowe, P Henderson, L Charlin… - arxiv preprint arxiv …, 2015‏ - arxiv.org
During the past decade, several areas of speech and language understanding have
witnessed substantial breakthroughs from the use of data-driven models. In the area of …

Do you mind? User perceptions of machine consciousness

AE Scott, D Neumann, J Niess… - Proceedings of the 2023 …, 2023‏ - dl.acm.org
The prospect of machine consciousness cultivates controversy across media, academia,
and industry. Assessing whether non-experts perceive technologies as conscious, and …

Simulating user satisfaction for the evaluation of task-oriented dialogue systems

W Sun, S Zhang, K Balog, Z Ren, P Ren… - Proceedings of the 44th …, 2021‏ - dl.acm.org
Evaluation is crucial in the development process of task-oriented dialogue systems. As an
evaluation method, user simulation allows us to tackle issues such as scalability and cost …

Speech act identification using semantic dependency graphs with probabilistic context-free grammars

JF Yeh - ACM Transactions on Asian and Low-Resource …, 2016‏ - dl.acm.org
We propose an approach for identifying the speech acts of speakers' utterances in
conversational spoken dialogue that involves using semantic dependency graphs with …

Gaussian processes for pomdp-based dialogue manager optimization

M Gašić, S Young - IEEE/ACM Transactions on Audio, Speech …, 2013‏ - ieeexplore.ieee.org
A partially observable Markov decision process (POMDP) has been proposed as a dialog
model that enables automatic optimization of the dialog policy and provides robustness to …

Experience replay-based deep reinforcement learning for dialogue management optimisation

S Malviya, P Kumar, S Namasudra… - Transactions on asian and …, 2022‏ - dl.acm.org
Dialogue policy is a crucial component in task-oriented Spoken Dialogue Systems (SDSs).
As a decision function, it takes the current dialogue state as input and generates appropriate …

Sample efficient deep reinforcement learning for dialogue systems with large action spaces

G Weisz, P Budzianowski, PH Su… - IEEE/ACM Transactions …, 2018‏ - ieeexplore.ieee.org
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 optimization …

Neural user simulation for corpus-based policy optimisation for spoken dialogue systems

F Kreyssig, I Casanueva, P Budzianowski… - arxiv preprint arxiv …, 2018‏ - arxiv.org
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 …