Notes:
Dialog management is the process of managing a conversation between a user and a computer system, such as a chatbot or voice assistant. It involves deciding what action to take in response to a user’s input, as well as keeping track of the context and state of the conversation.
Dialog management systems are often used to build chatbots and voice assistants that can engage in natural, human-like conversation with users. They are used in a variety of applications, such as customer service, education, and entertainment.
In order to build a dialog management system, you will need to design the conversation flow and define the possible actions that the system can take in response to user input. You may also need to use machine learning techniques to enable the system to understand and respond to user input in a natural and appropriate way.
There are several different approaches to dialog management, each with its own advantages and disadvantages. Some common approaches include:
- Rule-based dialog management: This approach involves defining a set of rules that determine how the system should respond to user input. The rules are typically based on the specific words or phrases that the user inputs, and the system responds according to the corresponding rule. Rule-based systems are relatively simple to build, but they can be limited in their ability to handle unexpected or unusual input.
- Machine learning-based dialog management: In this approach, the system is trained on a large dataset of example conversations, and it learns to predict the appropriate response to a given user input based on this training data. Machine learning-based systems can be more flexible and adaptable than rule-based systems, but they require a large amount of training data and may be more complex to build and maintain.
- Hybrid dialog management: This approach combines elements of both rule-based and machine learning-based dialog management. The system may use rules to handle certain types of input, while using machine learning to handle more open-ended or unstructured input. Hybrid systems can be more flexible and adaptable than pure rule-based systems, while still being simpler to build and maintain than pure machine learning-based systems.
There are also other approaches to dialog management, such as planning-based systems and hybrid systems that combine multiple approaches. The choice of approach will depend on the specific requirements and goals of the system being developed.
Neural dialog management is a type of machine learning-based dialog management that uses neural networks to model and generate responses to user input. It is similar to other machine learning-based approaches in that it involves training a model on a large dataset of example conversations, and using that model to predict appropriate responses to new input.
However, neural dialog management differs from other machine learning-based approaches in that it typically uses deep learning techniques, such as long short-term memory (LSTM) networks or transformer models, to process and understand user input. These techniques allow the system to capture more complex patterns and relationships in the data, and can enable the system to handle more open-ended or unstructured input.
One key difference between neural dialog management and other machine learning-based approaches is that neural dialog management systems are typically end-to-end models that can generate responses directly, without the need for a separate response generation step. This can make them more efficient and easier to deploy in a production setting.
References:
See also:
Dialog Management Middleware | Dialog Management Module | Dialog Manager | Dialog Management Frameworks | OwlSpeak
Continuously learning neural dialogue management
PH Su, M Gasic, N Mrksic, L Rojas-Barahona… – arXiv preprint arXiv …, 2016 – arxiv.org
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 by supervision from a set of dialogue data and then continuously improve its …
Corporate social performance and stakeholder dialogue management
JM Agudo?Valiente, C Garcés?Ayerbe… – Corporate Social …, 2015 – Wiley Online Library
This study analyses how firms act with regard to social responsibility from the perspective of Stakeholder Theory. The objective is to empirically analyse the importance of communication with stakeholders for social responsibility. This involves the establishment of …
Multimodal Dialogue Management for Multiparty Interaction with Infants
S Nasihati Gilani, D Traum, A Merla, E Hee… – Proceedings of the …, 2018 – dl.acm.org
We present dialogue management routines for a system to engage in multiparty agent-infant interaction. The ultimate purpose of this research is to help infants learn a visual sign language by engaging them in naturalistic and socially contingent conversations during an …
A hybrid approach to dialogue management based on probabilistic rules
P Lison – Computer Speech & Language, 2015 – Elsevier
We present a new modelling framework for dialogue management based on the concept of probabilistic rules. Probabilistic rules are defined as structured mappings between logical conditions and probabilistic effects. They function as high-level templates for probabilistic …
Sample-efficient actor-critic reinforcement learning with supervised data for dialogue management
PH Su, P Budzianowski, S Ultes, M Gasic… – arXiv preprint arXiv …, 2017 – arxiv.org
Deep reinforcement learning (RL) methods have significant potential for dialogue policy optimisation. However, they suffer from a poor performance in the early stages of learning. This is especially problematic for on-line learning with real users. Two approaches are …
Feudal Reinforcement Learning for Dialogue Management in Large Domains
I Casanueva, P Budzianowski, PH Su, S Ultes… – arXiv preprint arXiv …, 2018 – arxiv.org
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 dimensionality. We propose a novel Dialogue Management architecture, based on Feudal …
An overview of end-to-end language understanding and dialog management for personal digital assistants
R Sarikaya, PA Crook, A Marin, M Jeong… – … (SLT), 2016 IEEE, 2016 – ieeexplore.ieee.org
Spoken language understanding and dialog management have emerged as key technologies in interacting with personal digital assistants (PDAs). The coverage, complexity, and the scale of PDAs are much larger than previous conversational …
Strategic dialogue management via deep reinforcement learning
H Cuayáhuitl, S Keizer, O Lemon – arXiv preprint arXiv:1511.08099, 2015 – arxiv.org
Artificially intelligent agents equipped with strategic skills that can negotiate during their interactions with other natural or artificial agents are still underdeveloped. This paper describes a successful application of Deep Reinforcement Learning (DRL) for training …
Distributed dialogue policies for multi-domain statistical dialogue management
M Gaši?, D Kim, P Tsiakoulis… – Acoustics, Speech and …, 2015 – ieeexplore.ieee.org
Statistical dialogue systems offer the potential to reduce costs by learning policies automatically on-line, but are not designed to scale to large open-domains. This paper proposes a hierarchical distributed dialogue architecture in which policies are organised in …
Knowledge transfer between speakers for personalised dialogue management
I Casanueva, T Hain, H Christensen, R Marxer… – Proceedings of the 16th …, 2015 – aclweb.org
Abstract Model-free reinforcement learning has been shown to be a promising data driven approach for automatic dialogue policy optimization, but a relatively large amount of dialogue interactions is needed before the system reaches reasonable performance …
A domain-independent statistical methodology for dialog management in spoken dialog systems
D Griol, Z Callejas, R López-Cózar… – Computer Speech & …, 2014 – Elsevier
This paper proposes a domain-independent statistical methodology to develop dialog managers for spoken dialog systems. Our methodology employs a data-driven classification procedure to generate abstract representations of system turns taking into account the …
Sub-domain modelling for dialogue management with hierarchical reinforcement learning
P Budzianowski, S Ultes, PH Su, N Mrkši?… – arXiv preprint arXiv …, 2017 – arxiv.org
Human conversation is inherently complex, often spanning many different topics/domains. This makes policy learning for dialogue systems very challenging. Standard flat reinforcement learning methods do not provide an efficient framework for modelling such …
Interactive reinforcement learning for task-oriented dialogue management
P Shah, D Hakkani-Tür, L Heck – NIPS 2016 Deep Learning …, 2016 – research.google.com
Dialogue management is the component of a dialogue system that determines the optimal action for the system to take at each turn. An important consideration for dialogue managers is the ability to adapt to new user behaviors unseen during training. In this paper, we …
Spoken Conversational AI in Video Games–Emotional Dialogue Management Increases User Engagement
J Fraser, I Papaioannou, O Lemon – 2018 – researchgate.net
Many developers of today’s role-playing games strive to find a balance in creating a game that is both immersive and enjoyable to play [2, 3]. To better understand immersion in this setting, we can distinguish two different kinds of immersion: diegetic immersion, where the …
Adaptive dialogue management in the kristina project for multicultural health care applications
L Pragst, S Ultes, M Kraus… – Proceedings of the …, 2015 – pubman.mpdl.mpg.de
The goal of the EU-funded KRISTINA project is to help migrants in European countries get information about their resident country’s health care system by the means of a socially competent dialogue system. This system has to be able to handle a considerably large …
Users’ belief awareness in reinforcement learning-based situated human–robot dialogue management
E Ferreira, G Milliez, F Lefevre, R Alami – Natural Language Dialog …, 2015 – Springer
Others can have a different perception of the world than ours. Understanding this divergence is an ability, known as perspective taking in developmental psychology, that humans exploit in daily social interactions. A recent trend in robotics aims at endowing robots with similar …
Single-model multi-domain dialogue management with deep learning
A Papangelis, Y Stylianou – Advanced Social Interaction with Agents, 2019 – Springer
Abstract We present a Deep Learning approach to dialogue management for multiple domains. Instead of training multiple models (eg one for each domain), we train a single domain-independent policy network that is applicable to virtually any information-seeking …
Policy adaptation for deep reinforcement learning-based dialogue management
L Chen, C Chang, Z Chen, B Tan… – … on Acoustics, Speech …, 2018 – ieeexplore.ieee.org
Policy optimization is the core part of statistical dialogue management. Deep reinforcement learning has been successfully used for dialogue policy optimization for a static pre-defined domain. However, when the domain changes dynamically, eg a new previously unseen …
A Benchmarking Environment for Reinforcement Learning Based Task Oriented Dialogue Management
I Casanueva, P Budzianowski, PH Su, N Mrkši?… – arXiv preprint arXiv …, 2017 – arxiv.org
Dialogue assistants are rapidly becoming an indispensable daily aid. To avoid the significant effort needed to hand-craft the required dialogue flow, the Dialogue Management (DM) module can be cast as a continuous Markov Decision Process (MDP) and trained …
Metalogue: A multiperspective multimodal dialogue system with metacognitive abilities for highly adaptive and flexible dialogue management
J Alexandersson, M Aretoulaki… – Intelligent …, 2014 – ieeexplore.ieee.org
This poster paper presents a high-level description of the Metalogue project that is developing a multi-modal dialogue system that is able to implement interactive behaviors that seem natural to users and is flexible enough to exploit the full potential of multimodal …
Hyper-parameter optimisation of gaussian process reinforcement learning for statistical dialogue management
L Chen, PH Su, M Gasic – Proceedings of the 16th Annual Meeting of the …, 2015 – aclweb.org
Gaussian processes reinforcement learning provides an appealing framework for training the dialogue policy as it takes into account correlations of the objective function given different dialogue belief states, which can significantly speed up the learning. These …
Dialogue management for user-centered adaptive dialogue
S Ultes, H Dikme, W Minker – Situated Dialog in Speech-Based Human …, 2016 – Springer
A novel approach for introducing adaptivity to user satisfaction into dialogue management is presented in this work. In general, rendering the dialogue adaptive to user satisfaction enables the dialogue system to improve the course of the dialogue or to handle problematic …
Multidimensional dialogue management for tutoring systems
A Malchanau, V Petukhova, H Bunt… – Proceedings of the 7th …, 2015 – researchgate.net
In this paper we propose an approach to dialogue management for tutoring systems applications. We apply the information state update (ISU) machinery that operates on a multidimensional context model. This approach not only captures the behaviour of dialogue …
Rasa: Open source language understanding and dialogue management
T Bocklisch, J Faulker, N Pawlowski… – arXiv preprint arXiv …, 2017 – arxiv.org
We introduce a pair of tools, Rasa NLU and Rasa Core, which are open source python libraries for building conversational software. Their purpose is to make machine-learning based dialogue management and language understanding accessible to non-specialist …
Dialogue management: generative approaches to belief tracking
M Gašic – 2017 – mi.eng.cam.ac.uk
Page 1. Dialogue management: generative approaches to belief tracking Milica Gašic Dialogue Systems Group, Cambridge University Engineering Department February 7, 2017 1 / 37 Page 2. In this lecture… Dialogue management architecture Need for belief tracking Generative …
Adaptive grounding and dialogue management for autonomous conversational assistants for elderly users
R Yaghoubzadeh, K Pitsch, S Kopp – International Conference on …, 2015 – Springer
People with age-related or congenital cognitive impairments require assistance in daily tasks to enable them to maintain a self-determined lifestyle in their own home. We developed and evaluated a prototype of an autonomous spoken dialogue assistant to …
Exploring the applicability of elaborateness and indirectness in dialogue management
L Pragst, W Minker, S Ultes – Advanced Social Interaction with Agents, 2019 – Springer
In this paper, we investigate the applicability of soft changes to system behaviour, namely changing the amount of elaborateness and indirectness displayed. To this end, we examine the impact of elaborateness and indirectness on the perception of human-computer …
Optimizing human-interpretable dialog management policy using genetic algorithm
H Ren, W Xu, Y Yan – Automatic Speech Recognition and …, 2015 – ieeexplore.ieee.org
Automatic optimization of spoken dialog management policies that are robust to environmental noise has long been the goal for both academia and industry. Approaches based on reinforcement learning have been proved to be effective. However, the numerical …
Enhancing Military Helicopter Pilot Assistant Systems Through Resource Adaptive Dialogue Management
MA Vidulich, PS Tsang, J Flach – Advances in Aviation Psychology, 2016 – taylorfrancis.com
The Institute of Flight Systems (IFS) oversees a 20-year research agenda on knowledge-based assistant systems in vehicle guidance work processes that provide an alternative way of human-automation co-action. Such assistant systems have proven their potential to …
A novel factored POMDP model for affective dialogue management
F Ren, Y Wang, C Quan – Journal of Intelligent & Fuzzy …, 2016 – content.iospress.com
Partially observable Markov decision process (POMDP) model has been demonstrated many times to be suited for robust spoken dialogue management. Recently, some factored representations of POMDP model are designed for specific dialogue tasks. This paper …
Structured probabilistic modelling for dialogue management
P Lison – 2014 – duo.uio.no
This thesis presents a new modelling framework for dialogue management based on the concept of probabilistic rules. Probabilistic rules are defined as if… then… else constructions associating logical conditions on input variables to probabilistic effects over output variables …
An Ontology-Based Dialogue Management System for Virtual Personal Assistants
M Wessel, G Acharya, J Carpenter, M Yin – Proceedings of the 8th …, 2017 – uni-ulm.de
Dialogue management (DM) is a difficult problem. We present OntoVPA, an Ontology-Based Dialogue Management System (DMS) for Virtual Personal Assistants (VPA’s). The features of OntoVPA are offered as potential solutions to core DM problems. We illustrate OntoVPA’s …
flexdiam–Flexible dialogue management for incremental interaction with virtual agents (demo paper)
R Yaghoubzadeh, S Kopp – International Conference on Intelligent Virtual …, 2016 – Springer
We present a demonstration system for incremental spoken human–machine dialogue for task-centric domains that includes a controller for verbal and nonverbal behavior for virtual agents. The dialogue management components can handle uncertainty in input and resolve …
OntoVPA—An Ontology-Based Dialogue Management System for Virtual Personal Assistants
M Wessel, G Acharya, J Carpenter, M Yin – Advanced Social Interaction …, 2019 – Springer
Dialogue management (DM) is a difficult problem. We present OntoVPA, an Ontology-Based Dialogue Management System (DMS) for Virtual Personal Assistants (VPAs). The features of OntoVPA are offered as generic solutions to core DM problems, such as dialogue state …
A probabilistic framework for representing dialog systems and entropy-based dialog management through dynamic stochastic state evolution
J Wu, M Li, CH Lee – IEEE/ACM Transactions on Audio, Speech and …, 2015 – dl.acm.org
In this paper, we present a probabilistic framework for goal-driven spoken dialog systems. A new dynamic stochastic state (DS-state) is then defined to characterize the goal set of a dialog state at different stages of the dialog process. Furthermore, an entropy minimization …
TFSM?based dialogue management model framework for affective dialogue systems
F Ren, Y Wang, C Quan – IEEJ Transactions on Electrical and …, 2015 – Wiley Online Library
A new dialogue management model for affective dialogue system, which aims to provide a service of information inquiry and affective interaction, is proposed in this paper. First, we construct two finite state machines (TFSM) to model the user and the system, respectively …
Challenges for adaptive dialogue management in the KRISTINA project
L Pragst, J Miehle, W Minker, S Ultes – Proceedings of the 1st ACM …, 2017 – dl.acm.org
Access to health care related information can be vital and should be easily accessible. However, immigrants often have difficulties to obtain the relevant information due to language barriers and cultural differences. In the KRISTINA project, we address those …
Evolvable dialogue state tracking for statistical dialogue management
K Yu, L Chen, K Sun, Q Xie, S Zhu – Frontiers of Computer Science, 2016 – Springer
Statistical dialogue management is the core of cognitive spoken dialogue systems (SDS) and has attracted great research interest. In recent years, SDS with the ability of evolution is of particular interest and becomes the cuttingedge of SDS research. Dialogue state tracking …
An entropy minimization framework for goal-driven dialogue management
J Wu, M Li, CH Lee – Sixteenth Annual Conference of the …, 2015 – pdfs.semanticscholar.org
We propose an entropy minimization dialog management (DM) strategy for goal-driven information retrieval (IR). By associating each goal of an IR task with a set of stochastic attributes, reaching a goal can then be accomplished by filling the “attribute slots” …
Feudal Dialogue Management with Jointly Learned Feature Extractors
I Casanueva, P Budzianowski, S Ultes… – Proceedings of the 19th …, 2018 – aclweb.org
Reinforcement learning (RL) is a promising dialogue policy optimisation approach, but traditional RL algorithms fail to scale to large domains. Recently, Feudal Dialogue Management (FDM), has shown to increase the scalability to large domains by …
Topic switch models for dialogue management in virtual humans
W Zhu, A Chowanda, M Valstar – International Conference on Intelligent …, 2016 – Springer
This paper presents a novel data-driven Topic Switch Model based on a cognitive representation of a limited set of topics that are currently in-focus, which determines what utterances are chosen next. The transition model was statistically learned from a large set of …
Curriculum Learning Based on Reward Sparseness for Deep Reinforcement Learning of Task Completion Dialogue Management
A Saito – Proceedings of the 2018 EMNLP Workshop SCAI: The …, 2018 – aclweb.org
Learning from sparse and delayed reward is a central issue in reinforcement learning. In this paper, to tackle reward sparseness problem of task oriented dialogue management, we propose a curriculum based approach on the number of slots of user goals. This curriculum …
flexdiam–flexible dialogue management for problem-aware, incremental spoken interaction for all user groups (Demo paper)
R Yaghoubzadeh, S Kopp – … of the 7th Workshop on Speech …, 2016 – pub.uni-bielefeld.de
The dialogue management framework flexdiam was designed to afford people across a wide spectrum of cognitive capabilities access to a spoken-dialogue controlled assistive system, aiming for a conversational speech style combined with incremental feedback and …
A Case Study on the Importance of Belief State Representation for Dialogue Policy Management
M Kotti, V Diakoloukas, A Papangelis… – Proc. Interspeech …, 2018 – isca-speech.org
… 989 Page 5. 6. References [1] H. Hardy, T. Strzalkowski, and M. Wu, “Dialogue management for an automated multilingual call center,” in Proc. HLT-NAACL 2003 Workshop Research Directions in Dialogue Processing, May-June 2003, pp. 10–12 …
Combining Several User Models to Improve and Adapt the Dialog Management Process in Spoken Dialog Systems
D Griol, JM Molina, A Sanchis, Z Callejas – International Workshop on …, 2015 – Springer
Spoken dialog systems have demonstrated a high potential for more flexible, usable and natural human-computer interaction. These improvements are highly dependent on the users’ adaptation and dialog management processes, which respectively integrates …
Structural Optimization and Online Evolutionary Learning for Spoken Dialog Management
H Ren, Y Yan – IEEE Signal Processing Letters, 2016 – ieeexplore.ieee.org
Designing dialog management (DM) policies that are robust to environmental noises is a nontrivial task. Approaches based on reinforcement learning (RL) are popular in academia and have been empirically shown to exhibit much better performance than handcrafted …
Adaptive speech recognition and dialogue management for users with speech disorders
I Casanueva, H Christensen, T Hain… – … Annual Conference of …, 2014 – isca-speech.org
Spoken control interfaces are very attractive to people with severe physical disabilities who often also have a type of speech disorder known as dysarthria. This condition is known to decrease the accuracy of automatic speech recognisers (ASRs) especially for users with …
User-aware dialogue management policies over attributed bi-automata
M Serras, MI Torres, A del Pozo – Pattern Analysis and Applications, 2018 – Springer
Designing dialogue policies that take user behavior into account is complicated due to user variability and behavioral uncertainty. Attributed probabilistic finite-state bi-automata (A-PFSBA) have proven to be a promising framework to develop dialogue managers that …
Automatic modification of communication style in dialogue management
L Pragst, J Miehle, S Ultes… – Proceedings of the INLG …, 2016 – repositori.upf.edu
In task-oriented dialogues, there is often only one right answer the system can give. However, a lack of variation can seem repetitive and unnatural. Humans change the way they express something, eg by being more or less concise. We aim to approximate this …
From spoken language to ontology-driven dialogue management
D Mouromtsev, L Kovriguina, Y Emelyanov… – … Conference on Text …, 2015 – Springer
The paper describes the architecture of the prototype of the spoken dialogue system combining deep natural language processing with an information state dialogue manager. The system assists technical support to the customers of the digital TV provider. Raw data …
Policy optimization of dialogue management in spoken dialogue system for out-of-domain utterances
Y Xu, P Huang, J Tang, Q Huang… – Asian Language …, 2016 – ieeexplore.ieee.org
This paper addresses the policy optimization of a dialogue management scheme based on partially observable Markov decision processes (POMDP), which is designed for out-of-domain (OOD) utterances processing in spoken dialogue system. First, POMDP-Based DM …
Optimizing Policy via Deep Reinforcement Learning for Dialogue Management
G Xu, H Lee, MW Koo, J Seo – Big Data and Smart Computing …, 2018 – ieeexplore.ieee.org
In this paper, we propose a dialogue manager model based on Deep Reinforcement Learning, which automatically optimizes a dialogue policy. The policy is trained within deep Q-learning algorithm, which efficiently approximates value of actions given a large space of …
MADMACS-Multiadaptive Dialogue Management in Cyber-Physical Environments
Y Körber, V Hahn, MM Moniri… – … IE), 2017 International …, 2017 – ieeexplore.ieee.org
Today, cyber-physical environments (CPEs) are omnipresent-for instance as smart homes, cars, shopping environments, business facilities, Industrie 4.0 factories, and smart cities. Characterized by a large number of individual systems and devices with their sensors and …
User behavior fusion in dialog management with multi-modal history cues
M Yang, J Tao, L Chao, H Li, D Zhang, H Che… – Multimedia Tools and …, 2015 – Springer
It enhances user experience by making the talking avatar be sensitive to user behaviors in human computer interaction (HCI). In this study, we combine user’s multi-modal behaviors with behaviors’ historical information in dialog management (DM) to improve the avatar’s …
Assistive and Adaptive Dialog Management
F Nielsen, W Minker – Companion Technology, 2017 – Springer
One of the most important challenges in the field of human-computer interaction is maintaining and enhancing the willingness of the user to interact with the technical system. This willingness to cooperate provides a solid basis which is required for a collaborative …
Decision making strategies for finite-state bi-automaton in dialog management
F Ghigi, MI Torres – Natural Language Dialog Systems and Intelligent …, 2015 – Springer
Stochastic regular bi-languages has been recently proposed to model the joint probability distributions appearing in some statistical approaches of spoken dialog systems. To this end a deterministic and probabilistic finite-state bi-automaton was defined to model the …
Enhancing military helicopter pilot assistant systems through resource adaptive dialogue management
F Maiwald, A Schulte – Advances in Aviation Psychology, 2014 – books.google.com
The Institute of Flight Systems (IFS) oversees a 20-year research agenda on knowledge-based assistant systems in vehicle guidance work processes that provide an alternative way of human–automation co-action. Such assistant systems have proven their potential to …
Reinforest: Multi-domain dialogue management using hierarchical policies and knowledge ontology
T Zhao – 2016 – pdfs.semanticscholar.org
This report describes a dialog management framework that is designed to efficiently create multi-domain, mixed-initiative dialog system. We formalize the existing state-of-the-art plan-based RavenClaw dialog management framework [2] into a Semi-Markov Decision Process …
Dialogue management based on multi-domain corpus
W Ge, B Xu – Proceedings of the 16th Annual Meeting of the Special …, 2015 – aclweb.org
Dialogue Management (DM) is a key issue in Spoken Dialogue System. Most of the existing data-driven DM schemes train the dialogue policy for some specific domain (or vertical domain), only using the dialogue corpus in this domain, which might suffer from the scarcity …
Memory-augmented Dialogue Management for Task-oriented Dialogue Systems
Z Zhang, M Huang, Z Zhao, F Ji, H Chen… – arXiv preprint arXiv …, 2018 – arxiv.org
Dialogue management (DM) decides the next action of a dialogue system according to the current dialogue state, and thus plays a central role in task-oriented dialogue systems. Since dialogue management requires to have access to not only local utterances, but also the …
A Multiagent-Based Technique for Dialog Management in Conversational Interfaces
D Griol, JM Molina – Advances in Practical Applications of Scalable Multi …, 2016 – Springer
With the advances in Language Technologies and Natural Language Processing, conversational interfaces have begun to play an increasingly important role in the design of human-machine interaction systems in a number of devices and intelligent environments …
Probabilistic multiparty dialogue management for a game master robot
C Kennington, K Funakoshi, Y Takahashi… – Proceedings of the 2014 …, 2014 – dl.acm.org
We present our ongoing research on multiparty dialogue management for a game master robot which engages multiple human participants to play a quiz game. The robot invites passing people to join the game, instructs participants on the rules of the game, and leads …
A proposal to develop domain and subtask-adaptive dialog management models
D Griol, Z Callejas – … Annual Conference of the International Speech …, 2015 – isca-speech.org
Statistical dialog management techniques have the main advantage of allowing an easy adaptation of the dialog model to different application domains. In this paper we propose to also adapt the operation of the dialog manager to the different subtasks that conform the …
Platon: Dialog Management and Rapid Prototyping for Multilingual Multi-user Dialog Systems
M Gropp, A Schmidt, T Kleinbauer, D Klakow – … Conference on Text …, 2016 – Springer
We introduce Platon, a domain-specific language for authoring dialog systems based on Groovy, a dynamic programming language for the Java Virtual Machine (JVM). It is a fully-featured tool for dialog management that is also particularly suitable for, but not limited to …
A New Focus Strategy for Efficient Dialog Management
X Bao, Y Wu, X Lv – … Linguistics and Natural Language Processing Based …, 2016 – Springer
The dialog manager is the most important component for a dialog system, in which the dialog state tracking is crucial to a real-world system. We claim that the intractability of dialog states comes from two aspects: the large slot size in user’s goal and the large candidate …
User-centred spoken dialogue management
F Nothdurft, S Ultes, W Minker – Next Generation Intelligent Environments, 2016 – Springer
Adaptivity of intelligent environments to their surroundings provided by the ATRACO Spoken Dialogue Manager is only one means of adaptation. Recent work in Spoken Dialogue Systems focuses on the integration of user-centred adaptation means to alter the content …
Implementing Dialog Management
M McTear, Z Callejas, D Griol – The Conversational Interface, 2016 – Springer
There is a wide range of tools that support the generation of rule-based dialog managers for conversational interfaces. However, it is not as easy to find toolkits to develop statistical dialog managers based on reinforcement learning and/or corpus-based techniques. In this …
An Approach to Integrating Emotion in Dialogue Management
X Yuan – International Conference in Swarm Intelligence, 2015 – Springer
Presented in this paper is a method for the construction of emotion-enabled embodied (conversational) agents. By using a modified POMDP model, this method allows dialogue management not only to include emotion as part of the observation of user’s actions, but also …
THE ROLE OF A COGNITIVE BASED MODEL IN MULTIMODAL INTERACTION SYSTEMS DIALOGUE MANAGEMENT.
JS Prates, SJ Rigo, CA Costa… – … Journal on WWW …, 2016 – search.ebscohost.com
Abstract Researchers, in Multimodal Interaction Systems, devote substantial effort to the integration of external stimulus and signal, to the internal representation of this information and to the response generation. Nevertheless, they focus less effort on how to integrate …
A cooperative dialogue system for decision making based on statistical dialogue management
T Hiraoka – 2016 – isw3.naist.jp
Many researches in the dialogue research community have worked on the constructing goal-oriented dialogue system so far. However though, these previous researches focus on the situation where the dialogue system tries to achieve either the user goal or the system (or its …
Towards end-to-end learning for dialog state tracking and management using deep reinforcement learning
T Zhao, M Eskenazi – arXiv preprint arXiv:1606.02560, 2016 – arxiv.org
… Existing applications of RL to dialog management assume a given dialog state represen- tation … Page 4. Figure 2: An overview of the proposed end-to-end task-oriented dialog management framework. success labels with state tracking labels …
Dialog Management
M McTear, Z Callejas, D Griol – The Conversational Interface, 2016 – Springer
One of the core aspects in the development of conversational interfaces is to design the dialog management strategy. The dialog management strategy defines the system’s conversational behaviors in response to user utterances and environmental states. The …
Mathematical Model for Processing Multi-user Requests on POMDP Hybrid Dialog Management
S Koo, GG Lee, H Yu – Proceedings of the 10th International Conference …, 2016 – dl.acm.org
We present a mathematical model that integrates multiparty/multimodal components with a stochastic dialog model based on a partially observable Markov decision process (POMDP). Our suggested model consists of three subcomponents: a discrete input streamer, a dialog …
Dialogue management based on sentence clustering
W Ge, B Xu – Proceedings of the 53rd Annual Meeting of the …, 2015 – aclweb.org
Dialogue Management (DM) is a key issue in Spoken Dialogue System (SDS). Most of the existing studies on DM use Dialogue Act (DA) to represent semantic information of sentence, which might not represent the nuanced meaning sometimes. In this paper, we model DM …
Changing concepts of machine dialogue management
M Gnjatovi? – 2014 5th IEEE Conference on Cognitive …, 2014 – ieeexplore.ieee.org
An important research question in machine dialogue management is how to go beyond hand-crafted approaches. Currently, statistical approaches are prevalent. However, recently, researchers have focused again on the representational capacities of the human language …
Online Learning of Attributed Bi-Automata for Dialogue Management in Spoken Dialogue Systems
M Serras, MI Torres, A Del Pozo – Iberian Conference on Pattern …, 2017 – Springer
Online learning of dialogue managers is a desirable but often costly property to obtain. Probabilistic Finite State Bi-Automata (PFSBA) have shown to provide a flexible and adaptive framework to achieve this goal. In this paper, an Attributed PFSBA (A-PSFBA) is …
Policy optimization for spoken dialog management using genetic algorithm
H Ren, Q Zhao, Y Yan – IEICE TRANSACTIONS on Information and …, 2016 – search.ieice.org
The optimization of spoken dialog management policies is a non-trivial task due to the erroneous inputs from speech recognition and language understanding modules. The dialog manager needs to ground uncertain semantic information at times to fully understand …
Attentional top-down regulation and dialogue management in human-robot interaction
R Caccavale, A Finzi, L Lucignano, S Rossi… – Proceedings of the 2014 …, 2014 – dl.acm.org
We propose a framework where the human-robot interaction is modeled as a multimodal dialogue which is regulated by an attentional system that guides the system towards the execution of structured tasks. We introduce a simple case study to illustrate the system at …
Sequential Decision Making in Spoken Dialog Management
H Chinaei, B Chaib-draa – Building Dialogue POMDPs from Expert …, 2016 – Springer
This chapter includes two major sections. In Sect. 3.1, we introduce sequential decision making and study the supporting mathematical framework for it. We describe the Markov decision process (MDP) and the partially observable MDP (POMDP) frameworks, and …
Goal-Oriented Chatbot Dialog Management Bootstrapping with Transfer Learning
V Ilievski, C Musat, A Hossmann… – arXiv preprint arXiv …, 2018 – arxiv.org
Goal-Oriented (GO) Dialogue Systems, colloquially known as goal oriented chatbots, help users achieve a predefined goal (eg book a movie ticket) within a closed domain. A first step is to understand the user’s goal by using natural language understanding techniques. Once …
Multimodal constructions for dialogue management: On the role of eye gaze and gesture in dyadic and triadic interactions
G Brône, B Oben, J Vranjes, K Feyaerts – 2014 – lirias.kuleuven.be
It is a well-known fact that managing the flow of a dialogue in terms of sequentially organized speaker turns is a complex undertaking that requires a high degree of synchronized behavior across interlocutors. Early work in conversation analysis (eg …
A dialog management methodology based on evolving fuzzy-rule-based (frb) classifiers
D Griol, JA Iglesias, A Ledezma… – Evolving and Adaptive …, 2014 – ieeexplore.ieee.org
This paper proposes a statistical methodology based on evolving Fuzzy-rule-based (FRB) classifiers to develop dialog managers for spoken dialog systems. The dialog managers developed by means of our proposal select the next system action by considering a set of …
Dialogue management in task-oriented dialogue systems
P Blache – Proceedings of the 1st ACM SIGCHI International …, 2017 – dl.acm.org
This paper presents a new framework for implementing a dialogue manager, making it possible to infer new information in the course of the interaction as well as generating responses from the virtual agent. The approach relies on a specific organization of …
Finite-to-Infinite N-Best POMDP for Spoken Dialogue Management
G Wu, C Yuan, B Leng, X Wang – … Based on Naturally Annotated Big Data, 2015 – Springer
Abstract Partially Observable Markov Decision Process (POMDP) has been widely used as dialogue management in slot-filling Spoken Dialogue System (SDS). But there are still lots of open problems. The contribution of this paper lies in two aspects. Firstly, the observation …
Situation-and user-adaptive dialogue management
G Bertrand – 2015 – oparu.uni-ulm.de
In the sea of human machine interaction a growing trend to personalize the interaction experience has been surfacing over the last decades. Human machine interfaces have more and more become companion systems which on the one hand collect data about the user …
Towards online planning for dialogue management with rich domain knowledge
P Lison – Natural Interaction with Robots, Knowbots and …, 2014 – Springer
Most approaches to dialogue management have so far concentrated on offline optimisation techniques, where a dialogue policy is precomputed for all possible situations and then plugged into the dialogue system. This development strategy has however some limitations …
Application on Healthcare Dialog Management
H Chinaei, B Chaib-draa – Building Dialogue POMDPs from Expert …, 2016 – Springer
In this chapter, we show the application of our proposed methods on healthcare dialog management (Chinaei et al. 2014). That is, we use the methods in this book to learn a dialog POMDP from real dialogs of an intent-based dialog domain (cf. Chap. 1), known as SmartWheeler (Pineau …
Simple timing for probabilistic multiparty dialogue management
C Kennington, K Funakoshi… – … of Timing in Humin …, 2014 – pdfs.semanticscholar.org
We present ongoing work in multi-modal, multi-user dialogue management. We have developed a dialogue manager that can handle multiple human users for a game master robot and can simultaneously perceive its environment and perform actions. In this paper …
The evaluation of spoken dialog management models for multimodal HCIs.
R Maskeliunas – Int. Arab J. Inf. Technol., 2014 – ccis2k.org
The implementation of voice dialogs enables the realization of some of the aims of modern Human Computer Interaction (HCI) services more successfully and efficiently. Sadly the multimodal Lithuanian HCIs carried by the most natural form of communication-speech are …
A novel approach for data fusion and dialog management in user-adapted multimodal dialog systems
D Griol, J García, JM Molina – 2014 – e-archivo.uc3m.es
Multimodal dialog systems have demonstrated a high potential for more flexible, usable and natural humancomputer interaction. These improvements are highly dependent on the fusion and dialog management processes, which respectively integrates and interprets …
Analysing the Role of Social Media in Dialogue Marketing and Management as a Contemporary Franchising Local Area Marketing Technique
GB Webster, M Hume – Social Media Marketing: Breakthroughs in …, 2018 – igi-global.com
… Advancing previous work in LAM, this study analyses social media’s role as a contemporary LAM technique in Dialogue Marketing. It explores the use of Dialogue Management as a tool to enhance Dialogue Marketing for franchise businesses …
Chatbot with a Discourse Structure-Driven Dialogue Management
B Galitsky, D Ilvovsky – Proceedings of the Software Demonstrations of …, 2017 – aclweb.org
We build a chat bot with iterative content exploration that leads a user through a personalized knowledge acquisition session. The chat bot is designed as an automated customer support or product recommendation agent assisting a user in learning product …
Dialog Management using Active Learning Algorithms
PBJ Jie – 2016 – scholarbank.nus.sg
A dialog manager is a component of a dialog system that is responsible for the state and flow of the conversation. In this thesis, we explore the use of active learning for this task. For this thesis, the data we tested on is from a dialog system called “Let’s Go!”[Raux, Antoine, et …
Interrogative Sentence Generation and Dialogue Management in Intelligent Tutoring System
Z ZHANG, X SHANG – 2015 – atlantis-press.com
Intelligent tutoring is a hot field in the study of information-based teaching. This paper proposed a series of methods for building ITS in training of operational regulation domain. To make the dialog between system and users more intelligent, a frame-based knowledge …
Reinforcement Learning for Turn-Taking Management in Incremental Spoken Dialogue Systems.
H Khouzaimi, R Laroche, F Lefèvre – IJCAI, 2016 – ijcai.org
… A mixed initiative strategy (non-incremental baseline) is used for the dialogue management in order to gather all the slots: first the user for- mulates a complete request in natural language and if there are still missing information slots, the system asks for them one by one like in …
Lifestyle Agent: The Chat-Oriented Dialogue System for Lifestyle Management
H Kawata, K Ookawara, M Muta, S Masuko… – International Conference …, 2017 – Springer
… planning to promote improvement of lifestyle habits. Keywords. Lifestyle improvement Chat communication Rule-based dialogue management. Download fulltext PDF. 1 Introduction. Because lifestyle diseases account for the …
Dialogue Management in Spoken Dialogue System with Visual Feedback
W Ge, B Xu – Pacific Rim International Conference on Artificial …, 2014 – Springer
Dialogue Management (DM) is an essential issue in Spoken Dialogue Systems (SDS). Most of previous studies on DM do not consider the visual feedback from machine to user that could accelerate the dialogue process dramatically. Thus, in this paper, we firstly model the …
Personalised Dialogue Management for Users with Speech Disorders
I Casanueva – 2017 – core.ac.uk
Many electronic devices are beginning to include Voice User Interfaces (VUIs) as an alternative to conventional interfaces. VUIs are especially useful for users with restricted upper limb mobility, because they cannot use keyboards and mice. These users, however …
IQ-adaptive statistical dialogue management using Gaussian processes
J Miehle – 2017 – oparu.uni-ulm.de
Adapting a Spoken Dialogue System to the user’s satisfaction is supposed to result in more successful dialogues. In this thesis, Gaussian processes are used to model a policy for a statistical Spoken Dialogue System and the Interaction Quality (IQ) metric which is a …
Dialogue Summary: Management of Spasticity following Traumatic Brain Injury. Melbourne, Australia: NTRI Forum, November 2014
K Scott, L Piccenna, RL Gruen, P Bragge – 2014 – researchgate.net
… ISBN 978-0-9941593-4-2 Dialogue: The stakeholder dialogue ‘Management of Spasticity Following Traumatic Brain Injury’ was held on 27 October 2014 at the Monash University Conference Centre, Melbourne Australia. Copyright © Monash University 2014. All rights reserved …
Statistical Dialog Management for Health Interventions
U Yasavur – 2014 – digitalcommons.fiu.edu
Research endeavors on spoken dialogue systems in the 1990s and 2000s have led to the deployment of commercial spoken dialogue systems (SDS) in microdomains such as customer service automation, reservation/booking and question answering systems. Recent …
Utilizing deception information for dialog management of doctor-patient conversations.
K YOSHINO, S SAKTI, S NAKAMURA – ???????????? …, 2018 – jstage.jst.go.jp
?? Almost all of existing negotiation systems assume that their interlocutors (the user) are telling the truth. However, in negotiations, participants can tell lies to earn a profit. In this research, we proposed a negotiation dialog management system that detects user’s lies and …
Towards Dialogue Strategies for Cognitive Workload Management
J Villing – 2015 – gupea.ub.gu.se
Page 1. Towards Dialogue Strategies for Cognitive Workload Management Jessica Villing The Graduate School of Language Technology Page 2. Towards Dialogue Strategies for Cognitive Workload Management Page 3. Towards Dialogue Strategies for Cognitive Workload …
Module for Dialog Management in the Interaction System Between User and Mobile Robotic Guide
IM Kobozeva, AV Zimmerling – Trudy SPIIRAN, 2014 – mathnet.ru
The paper presents dialogue management module for a mobile robot as a guide. The model of the dialog management is presented as a network of transitions between states depending on two factors: visual and communicative. Details of the dialogue management …
An Ontology-Based Dialogue Management System for Banking and Finance Dialogue Systems
D Altinok – arXiv preprint arXiv:1804.04838, 2018 – arxiv.org
Keeping the dialogue state in dialogue systems is a notoriously difficult task. We introduce an ontology-based dialogue manage (OntoDM), a dialogue manager that keeps the state of the conversation, provides a basis for anaphora resolution and drives the conversation via …
Multimodal resources for the management of turn-taking in interpreter-mediated dialogue: An eye-tracking study
J Vranjes – 2017 – lirias.kuleuven.be
… mediated dialogues. The study also shows how verbal and non-verbal resources interact in the constitution of dialogue management and illustrates the importance of visual monitoring of the speaker’s embodied behavior. And …
Bayes By Backprop Neural Networks for Dialogue Management
C Tegho – 2017 – pdfs.semanticscholar.org
In dialogue management for statistical spoken dialogue systems, an agent learns a policy that maps a belief state to an action for the system to perform. Efficient exploration is key to successful dialogue policy estimation. Current deep reinforcement learning methods are …
Multi-label Topic Classification of Turkish Sentences Using Cascaded Approach for Dialog Management System
G So?anc?o?lu, B Köro?lu, O A??n – 2016 – tsdconference.org
In this paper, we propose a two-stage system which aims to classify utterances of customers into 10 categories including daily language and specific banking problems. Detecting the topic of customer question would enable the dialogue system to find the corresponding …
Dialogue Systems and Dialogue Management
D Burgan – 2016 – dtic.mil
A spoken dialogue system (SDS) is a specialised form of computer system that operates as an interface between users and the application, using spoken natural language as the primary means of communication. The motivation for spoken interaction with such systems is …
Dialogue as Shared Social Space in Management and Organizations
CC Rohn, U Sutrich – Leadership. Learning for the Future, 2014 – books.google.com
… speed C. chapter ROHN of projects knowledge seeks Modern and to and large establish business decision-making numbers© and is R of frequently explain stakeholders processes the 0 characterized O links from 1 in F S IA P 2 3 between dialogue, management and by the …
Towards a Persuasive Dialog System Supporting Personal Health Management
V Götzmann – National Research Center, 2015 – isl.anthropomatik.kit.edu
… 9 3. Introduction to the Health Assistant System 11 3.1. Application Scenario . . . . . 11 3.2. Applied Dialog Management Principles . . . . . 12 3.3. Usage Environment …