A dialogue manager for efficient adaptive man-machine dialogues

Evaluation of a dialogue manager for a mobile robot

2013 IEEE RO-MAN ◽

10.1109/roman.2013.6628466 ◽

2013 ◽

Cited By ~ 1

Author(s):

Marcelo Quindere ◽

Luis Seabra Lopes ◽

Antonio J. S. Teixeira

Keyword(s):

Mobile Robot ◽

Dialogue Manager

Joint On-line Learning of a Zero-shot Spoken Semantic Parser and a Reinforcement Learning Dialogue Manager

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ◽

10.1109/icassp.2019.8683274 ◽

2019 ◽

Cited By ~ 1

Author(s):

Matthieu Riou ◽

Bassam Jabaian ◽

Stephane Huet ◽

Fabrice Lefevre

Keyword(s):

Reinforcement Learning ◽

On Line ◽

Dialogue Manager ◽

On Line Learning

Multimodal dialogue system with NAO and VoiceXML dialogue manager

2017 8th IEEE International Conference on Cognitive Infocommunications (CogInfoCom) ◽

10.1109/coginfocom.2017.8268286 ◽

2017 ◽

Cited By ~ 3

Author(s):

Stanislav Ondas ◽

Jozef Juhar ◽

Matus Pleva ◽

Peter Fercak ◽

Rastislav Husovsky

Keyword(s):

Dialogue System ◽

Dialogue Manager ◽

Multimodal Dialogue

A Generic Spoken Dialogue Manager Applied to an Interactive 2D Game

Lecture Notes in Computer Science - Perception in Multimodal Dialogue Systems ◽

10.1007/978-3-540-69369-7_2 ◽

2008 ◽

pp. 2-13 ◽

Cited By ~ 2

Author(s):

Andrea Corradini ◽

Christer Samuelsson

Keyword(s):

Spoken Dialogue ◽

Dialogue Manager

Dialogue Manager for a NLIDB for Solving the Semantic Ellipsis Problem in Query Formulation

Knowledge-Based and Intelligent Information and Engineering Systems - Lecture Notes in Computer Science ◽

10.1007/978-3-642-15390-7_21 ◽

2010 ◽

pp. 203-213 ◽

Cited By ~ 3

Author(s):

Rodolfo A. Pazos R. ◽

Juan C. Rojas P. ◽

René Santaolaya S. ◽

José A. Martínez F. ◽

Juan J. Gonzalez B.

Keyword(s):

Query Formulation ◽

Dialogue Manager

A Dialogue Manager for a WWW-Based Information Retrieval System

Flexible Query Answering Systems ◽

10.1007/978-3-7908-1834-5_55 ◽

2001 ◽

pp. 592-601

Author(s):

Paulo Quaresma ◽

Irene Pimenta Rodrigues

Keyword(s):

Information Retrieval ◽

Retrieval System ◽

Information Retrieval System ◽

Dialogue Manager

HIS-OwlSpeak: A Model-Driven Dialogue Manager with Multiple Control Modes

2013 9th International Conference on Intelligent Environments ◽

10.1109/ie.2013.36 ◽

2013 ◽

Author(s):

Stefan Ultes ◽

Wolfgang Minker

Keyword(s):

Multiple Control ◽

Model Driven ◽

Dialogue Manager

Implementing Social Filter Rules in a Dialogue Manager Using Statecharts

Intelligent Virtual Agents - Lecture Notes in Computer Science ◽

10.1007/978-3-540-85483-8_50 ◽

2008 ◽

pp. 474-475

Author(s):

Jenny Brusk

Keyword(s):

Dialogue Manager ◽

Filter Rules

A tractable hybrid DDN–POMDP approach to affective dialogue modeling for probabilistic frame-based dialogue systems

Natural Language Engineering ◽

10.1017/s1351324908005032 ◽

2009 ◽

Vol 15 (2) ◽

pp. 273-307 ◽

Cited By ~ 29

Author(s):

TRUNG H. BUI ◽

MANNES POEL ◽

ANTON NIJHOLT ◽

JOB ZWIERS

Keyword(s):

Affective State ◽

Observation Error ◽

Dialogue Systems ◽

Dialogue Model ◽

Management Domain ◽

Novel Approach ◽

Look Ahead ◽

Markov Decision ◽

The One ◽

Dialogue Manager

AbstractWe propose a novel approach to developing a tractable affective dialogue model for probabilistic frame-based dialogue systems. The affective dialogue model, based on Partially Observable Markov Decision Process (POMDP) and Dynamic Decision Network (DDN) techniques, is composed of two main parts: the slot-level dialogue manager and the global dialogue manager. It has two new features: (1) being able to deal with a large number of slots and (2) being able to take into account some aspects of the user's affective state in deriving the adaptive dialogue strategies. Our implemented prototype dialogue manager can handle hundreds of slots, where each individual slot might have hundreds of values. Our approach is illustrated through a route navigation example in the crisis management domain. We conducted various experiments to evaluate our approach and to compare it with approximate POMDP techniques and handcrafted policies. The experimental results showed that the DDN–POMDP policy outperforms three handcrafted policies when the user's action error is induced by stress as well as when the observation error increases. Further, performance of the one-step look-ahead DDN–POMDP policy after optimizing its internal reward is close to state-of-the-art approximate POMDP counterparts.

A Conventional Dialogue Model Based on Dialogue Patterns

International Journal of Artificial Intelligence Tools ◽

10.1142/s0218213017600090 ◽

2017 ◽

Vol 26 (01) ◽

pp. 1760009 ◽

Cited By ~ 2

Author(s):

Guillaume Dubuisson Duplessis ◽

Alexandre Pauchet ◽

Nathalie Chaignaud ◽

Jean-Philippe Kotowicz

Keyword(s):

Open Source ◽

Software Agent ◽

Management Process ◽

Dialogue Model ◽

Dialogue Management ◽

Dialogue Games ◽

Human Interactions ◽

Model Based ◽

Dialogue Game ◽

Dialogue Manager

Our work aims at designing a dialogue manager dedicated to agents that interact with humans. In this article, we investigate how dialogue patterns at the dialogue act level extracted from Human-Human interactions can be fruitfully used by a software agent to interact with a human.We show how these patterns can be leveraged via a dialogue game structure in order to benefit to the dialogue management process of an agent. We describe how empirically specified dialogue games can be employed on both interpretative and generative levels of dialogue management. We present Dogma, an open-source module that can be used by an agent to manage its conventional communicative behaviour. We show that our library of dialogue games can be used into Dogma to generate fragments of dialogue that are strongly coherent from a human perspective.