Dialog Management for Decision Processes

The search for a standardized optimum way to communicate using natural language dialog has involved a lot of research. However, due to the diversity of communication domains, we think that this is extremely difficult to achieve and different dialogue management techniques should be applied for different situations. Our work presents the basis of a communication mechanism that supports decision processes, is based on decision trees, and minimizes the number of steps (turn-takes) in the dialogue. The initial dialog workflow is automatically generated and the user's interaction with the system can also change the decision tree and create new dialog paths with optimized cost. The decision tree represents the chronological ordering of the actions (via the parent-child relationship) and uses an object frame to represent the information state (capturing the notion of context). This paper presents our framework, the formalism for interaction and dialogue, and an evaluation of the system compared to relevant dialog planning frameworks (i.e. finite state diagrams, framebased, information state and planning-based dialogue systems).

2013

We present Dialog Moves Markup Language (DMML): an extensible markup language (XML) representation of modality independent communicative acts of automated conversational agents. In our architecture, DMML is the interface to and from conversational dialog managers for user interactions through any channel or modality. The use of a common XML interface language across different channels promotes high cost efficiency for the business. DMML itself has no application or domain specific elements; DMML elements embed elements representing application business logic. DMML captures the abstractions necessary to represent arbitrary multi-agent dialogs and to build cost-efficient, sophisticated natural language dialog systems for business applications. PDA

2006 IEEE Spoken Language Technology Workshop, 2006

Dialog interaction in conversational applications is subordinated to the goal of completing a domain-specific task. In this paper we present a basic architecture, a knowledge representation system, and a planning algorithm for dialogue management that decouples the interaction process from the planning task. In our system, the interaction is driven by the planner. We use logic programming, automatic planning and problem solving algorithms for representing information states and performing interaction management in the dialogue system. Our approach leverages recent advances in formalisms, inference engines, planning and problem solving, and is particularly suitable when implementing negotiation-intensive conversational applications.

One of the main limitations in existent domain-independent conver- sational agents is that the general and linguistic knowledge of these agents is limited to what the agents' developers explicitly defined. Therefore, a system which analyses user input at a deeper level of abstraction which backs its knowledge with common sense information will essentially result in a system that is capable of providing more adequate responses which in turn result in a better overall user experience. From this premise, a framework was proposed, and a working prototype was implemented upon this framework. These make use of various natural language processing tools, online and offline knowledge bases, and other information sources, to enable it to comprehend and construct relevant responses.

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2019

Complex domains demand task-oriented dialog system (TODS) to be able to reason and engage with humans in dialog and in information retrieval. This may require contemporary dialog systems to have improved conversation handling capabilities. One stating point is supporting conversations which logically advances, such that they could be able to handle sub dialogs meant to elicit more information, within a topic. This paper presents some findings on the research that has been carried out by the authors with regard to highlighting this problem and suggesting a possible solution. A solution which intended to minimize heavy reliance on handcrafts which have varying challenges. The study discusses an experiment for evaluating a novel architecture envisioned to improve this conversational requirement. The experiment results clearly depict the extent to which we have achieved this desired progression, the underlying effects to users and the potential implications to application. The study recommends combining Agency and Reinforcement learning to deliver the solution and could guide future studies towards achieving even more natural conversations.

Natural Language Engineering, 1997

Natural language interfaces require dialogue models that allow for robust, habitable and efficient interaction. This paper presents such a model for dialogue management for natural language interfaces. The model is based on empirical studies of human computer interaction in various simple service applications. It is shown that for applications belonging to this class the dialogue can be handled using fairly simple means. The interaction can be modeled in a dialogue grammar with information on the functional role of an utterance as conveyed in the linguistic structure. Focusing is handled using dialogue objects recorded in a dialogue tree representing the constituents of the dialogue. The dialogue objects in the dialogue tree can be accessed by the various modules for interpretation, generation and background system access. Focused entities are modeled in entities pertaining to objects or sets of objects, and related domain concept information; properties of the domain objects. A sim...

2004

Natural Language Understanding Systems (NLU) will not be widely deployed unless they are technically mature and cost effective to develop. Cost effective development hinges on the availability of tools and techniques enabling the rapid production of NLU applications through minimal human resources. Further, these tools and techniques should allow quick development of applications in a user friendly way and should be easy to upgrade in order to continuously follow the evolving technologies and standards. This paper presents a visual tool for the structuring and editing of dialog forms, the key element of driving conversation in NLU applications based on IBM technology. The main focus is given on the basic component used to describe Human -Machine interactions of that kind, the Dialogue Manager. In essence, the description of a tool that enables the visual representation of the Dialogue Manager mainly during the implementation phase is illustrated.

CHI Conference on Human Factors in Computing Systems Extended Abstracts

Spoken dialog systems, lacking the means to address the complex phenomena of spontaneous speech and conversational dynamics, force users into a constrained mode of dialog that resembles textbased interaction more closely than spoken conversation. Turntaking is simplified and discourse-related information is lost, as discourse markers are largely ignored and prosodic information is not captured or utilized. We hypothesize that incorporating a few of these key conversational phenomena at specific points in a dialog will reduce cognitive load in spoken human-computer interaction and expand the potential application areas of dialog systems to tasks requiring more complex interactions. In this paper, we describe our approach to adding conversational intelligence to dialog systems and our work to date validating the hypothesis that adding conversational intelligence to existing dialog systems will significantly reduce users' cognitive load. CCS CONCEPTS • Human-centered computing → Human computer interaction (HCI); Interaction paradigms; Natural language interfaces; Human computer interaction (HCI); HCI design and evaluation methods; User studies; • Computing methodologies → Artificial intelligence; Natural language processing.

1995

This paper presents an action scheme for dia logue management for natural language inler faces The scheme guides a dialogue manager which directs the interface's dialogue with the user communicates with the background system, and assists the interpretation and gets eration modules The dialogue manager was designed on the basis of an investigation of empirical material collected in Wizard of Oz experiments The empirical investigations re vealed that in dialogues with database systems users specify an object, or a set of objects and ask for domain concept information, e g the value of a property of that object or set of ob|ects The interface responds 1 perform ing the appropriate action e g providing the requited information or initiating a clarified lion subdialogue The action to bt carried out by the interface can be determined based on how objects and properties are specified from information in the user utterance the dialogue context and the response from the background system and its domain model J0NSSON