Natural Language Dialogue Research Articles

Marlowe, Prospero & la technologie litteraire

Marlowe, Prospero and Literary Technology: An author, an experimenter and a reviewer of the computer programs, Marlowe and Prospero, contribute in this article, respectively and successively, an extensive and detailed presentation of Marlowe, a report on what it is like to interact with Marlowe and a review of the recently-published work, by the first author, describing the development of Prospero for the Analyse of complex dossiers of texts conceming a social controversy, and Prospero's extension and adaptation with Marlowe to direct natural language dialog with researchers concerning specific complex dossiers.

Natural Language Assistant: A Dialog System for Online Product Recommendation

With the emergence of electronic-commerce systems, successful information access on electroniccommerce web sites becomes essential. Menu-driven navigation and keyword search currently provided by most commercial sites have considerable limitations because they tend to overwhelm and frustrate users with lengthy, rigid, and ineffective interactions. To provide an efficient solution for information access, we have built the NATURAL language ASSISTANT (NLA), a web-based natural language dialog system to help users find relevant products on electronic-commerce sites. The system brings together technologies in natural language processing and human-computer interaction to create a faster and more intuitive way of interacting with web sites. By combining statistical parsing techniques with traditional AI rule-based technology, we have created a dialog system that accommodates both customer needs and business requirements. The system is currently embedded in an application for recommending laptops and was deployed as a pilot on IBM's web site.

The Syrinx Spoken Language System

This paper describes the Syrinx Spoken Language System (Sylan), an automated dialogue system that is fully integrated with the Syrinx Large Vocabulary Speech Recogniser (Sycon) into the Syrinx SpeechMaster platform. This platform combines speech recognition, natural language processing, dialogue management, telephony and database integration into a robust and flexible Voice User Interface that permits the deployment of natural language dialogue systems in automated call centres. We first describe the architecture of Sylan which, being modular, allows us to build a system whose domain-independent components are reusable from application to application. We then present those components from the point of view of application developers, describing the data structures used by the system and the utilities to build them. The two prototypes that have already been developed using Sylan are briefly presented, and we conclude by drawing the lessons learned along the way and pointing to further research directions.

Invoking Emotions in a Dialog System based on Word-Impressions

There have been some studies about spoken natural language dialog,and most of them have successfully been developed within the speci ed task domains. However,current human-computer interfaces only get the data to process their programs.If the dialog processing has emotion comprehensive faculties, it should lead us to more human-like performance.In this paper,we present a method for constructing an emotion-handling dialog system in order to facilitate more confortable interaction with the users. We describe how to calculate emotions from the utterances,focusing on the similarities between the grammar structures and the semantic structures within the case frame.We made emotion generating calculations(EGC)to generate pleasure/displeasure emotion from an event.We also calculate the degree of the pleasure/displeasure from an opposite angle's length of the rectangular parallelepiped consisting of the all the terms in the EGC.EGC uses 8 type calculations for 12 event classi ed type by Okada. Word impressions about like/dislike are used for their calculations.Furthermore,we apply these calculations to the negatives and the noun phrases.To verify the e ectiveness of the proposed method,we tested some conversations using WWW-based health service system for elderly. We applied our method to 80 event in the conversations and calculated emotions almost corresponded to human-generating emotions.

大規模災害救助シミュレータを対象としたリアルタイム実況の自動生成

We address the problem of information flow in disaster relief scenarios by presenting an architecture for generating natural language dialogue between large numbers of agents. This architecture is the first step towards real-time support systems for relief workers and their controllers. Our work demonstrates how natural generation techniques from the MIKE commentary system for RoboCup soccer can be carried over to that of RoboCup Rescue. Thanks to this background, the initial product of our research is a system that explains a RoboCup Rescue simulation not to the agents in the domain themselves but to a watching audience. This ”commentary” is produced by recreating the actual dialogues most likely be occurring in the domain: walkie-talkie-conversations.

Intelligent Help Systems for UNIX

In this international collection of papers there is a wealth of knowledge on artificial intelligence (AI) and cognitive science (CS) techniques applied to the problem of providing help systems mainly for the UNIX operating system. The research described here involves the representation of technical computer concepts, but also the representation of how users conceptualise such concepts. The collection looks at computational models and systems such as UC, Yucca, and OSCON programmed in languages such as Lisp, Prolog, OPS-5, and C which have been developed to provide UNIX help. These systems range from being menu-based to ones with natural language interfaces, some providing active help, intervening when they believe the user to have misconceptions, and some based on empirical studies of what users actually do while using UNIX. Further papers investigate planning and knowledge representation where the focus is on discovering what the user wants to do, and figuring out a way to do it, as well as representing the knowledge needed to do so. There is a significant focus on natural language dialogue where consultation systems can become active, incorporating user modfelling, natural language generation and plan recognition, modelling metaphors, and users' mistaken beliefs. Much can be learned from seeing how AI and CS techniques can be investigated in depth while being applied to a real test-bed domain such as help on UNIX.

The Role of a Natural Language Conversational Interface in Online Sales: A Case Study

This paper describes the evaluation of a natural language dialog-based navigation system (HappyAssistant) that helps users access e-commerce sites to find relevant information about products and services. The prototype system leverages technologies in natural language processing and human-computer interaction to create a faster and more intuitive way of interacting with websites, especially for less experienced users. The result of a comparative study shows that users prefer the natural language-enabled navigation two to one over the menu driven navigation. In addition, the study confirmed the efficiency of using natural language dialog in terms of the number of clicks and the amount of time required to obtain the relevant information. In the case study, as compared to the menu driven system, the average number of clicks used in the natural language system was reduced by 63.2% and the average time was reduced by 33.3%.

Designing the User Interface for Multimodal Speech and Pen-Based Gesture Applications: State-of-the-Art Systems and Future Research Directions

The growing interest in multimodal interface design is inspired in large part by the goals of supporting more transparent, flexible, efficient, and powerfully expressive means of human-computer interaction than in the past. Multimodal interfaces are expected to support a wider range of diverse applications, be usable by a broader spectrum of the average population, and function more reliably under realistic and challenging usage conditions. In this article, we summarize the emerging architectural approaches for interpreting speech and pen-based gestural input in a robust manner-including early and late fusion approaches, and the new hybrid symbolic-statistical approach. We also describe a diverse collection of state-of-the-art multimodal systems that process users' spoken and gestural input. These applications range from map-based and virtual reality systems for engaging in simulations and training, to field medic systems for mobile use in noisy environments, to web-based transactions and standard text-editing applications that will reshape daily computing and have a significant commercial impact. To realize successful multimodal systems of the future, many key research challenges remain to be addressed. Among these challenges are the development of cognitive theories to guide multimodal system design, and the development of effective natural language processing, dialogue processing, and error-handling techniques. In addition, new multimodal systems will be needed that can function more robustly and adaptively, and with support for collaborative multiperson use. Before this new class of systems can proliferate, toolkits also will be needed to promote software development for both simulated and functioning systems.

Towards best practice in the development and evaluation of speech recognition components of a spoken language dialog system

This article provides a global overview of the main aspects of current practice in the design, implementation and evaluation of speech recognition components for Spoken Language Dialog Systems (SLDSs), and presents the results of the DISC European project related to speech recognition. DISC and its successor DISC-2 are efforts towards the definition of best practice guidelines for SLDS development and evaluation. SLDSs aim at using natural spoken input for performing an information processing task such as automated standards, call routing or travel planning and reservations. The main functionality of an SLDS are speech recognition, natural language understanding, dialog management, database access and interpretation, response generation and speech synthesis. Speech recognition, which transforms the acoustic signal into a string of words, is a key technology in any SLDS.

Best practice in spoken language dialogue systems engineering:

This special issue brings together representative views on what has come to be known as in the development and evaluation of spoken language dialogue systems (SLDSs). The issue was initiated in the context of the European Esprit project DISC, which ran from June 1997 till February 2000. DISC's main goal was to identify current practice in both the development and the evaluation of SLDSs, in order to arrive at a useful definition and description of best practice. The project has resulted in a collection of guidelines which are intended for different target groups, in particular developers, deployers and customers. The last few years the interest in SLDSs has increased enormously. At present there is a large number of systems available, many of them for commercial use. Their number is growing rapidly, and so are the variety of their functionalities and the diversity of their application domains. The tasks that advanced systems are able to perform are often more complex, less stereotypical, and are often carried out in the context of several interconnected domains of application. With these advances have come higher expectations of the naturalness and intelligence with which SLDSs fulfill their assignments, and as a consequence the interest in such systems has even grown more, both within academic and commercial circles. As far as natural human- system interaction is concerned, one significant change in SLDS design concerns the interaction between natural language understanding and dialogue management. Here we see a clear tendency towards models that incorporate a substantial amount of discourse semantics and make use of some conception of context-change. This allows for more natural interactions between the system and its human users, due on the one hand to the system's improved ability to compute the intended meaning of the user's input and on the other to the increased sophistication of the strategies it uses for planning its own responses. Such improved capacities are crucial when the system is to leave more of the initiative to the user, instead of keeping the dialogue on a narrowly circumscribed path of largely predictable exchanges. Further, there is a tendency to combine spoken language human-system interaction with other modalities of information exchange and representation (e.g., images and gestures), asking for both modality-specific and modality-integrating syntactic and semantic processing capabilities. All these developments have led to a situation in which there is a great need, shared by developers, deployers and customers alike, for effective guidelines, which will enable them to make accurate and successful design and implementation decisions, in accordance with broad consensus of what must be best practice in this particular engineering domain.

Speech and language processing for next-millennium communications services

In the future, the world of telecommunications will be vastly different than it is today. The driving force will be the seamless integration of real time communications (e.g. voice, video, music, etc.) and data into a single network, with ubiquitous access to that network anywhere, anytime, and by a wide range of devices. The only currently available ubiquitous access device to the network is the telephone, and the only ubiquitous user access technology mode is spoken voice commands and natural language dialogues with machines. In the future, new access devices and modes will augment speech in this role, but are unlikely to supplant the telephone and access by speech anytime soon. Speech technologies have progressed to the point where they are now viable for a broad range of communications services, including: compression of speech for use over wired and wireless networks; speech synthesis, recognition, and understanding for dialogue access to information, people, and messaging; and speaker verification for secure access to information and services. The paper provides brief overviews of these technologies, discusses some of the unique properties of wireless, plain old telephone service, and Internet protocol networks that make voice communication and control problematic, and describes the types of voice services available in the past and today, and those that we foresee becoming available over the next several years.

Natural language dialogue for personalized interaction

article Free Access Share on Natural language dialogue for personalized interaction Authors: Wlodek Zadrozny IBM T. J. Watson Research Center, Hawthorne, NY IBM T. J. Watson Research Center, Hawthorne, NYView Profile , M. Budzikowska IBM T. J. Watson Research Center, Hawthorne, NY IBM T. J. Watson Research Center, Hawthorne, NYView Profile , J. Chai IBM T. J. Watson Research Center, Hawthorne, NY IBM T. J. Watson Research Center, Hawthorne, NYView Profile , N. Kambhatla IBM T. J. Watson Research Center, Hawthorne, NY IBM T. J. Watson Research Center, Hawthorne, NYView Profile , S. Levesque IBM Canada IBM CanadaView Profile , N. Nicolov IBM T. J. Watson Research Center, Hawthorne, NY IBM T. J. Watson Research Center, Hawthorne, NYView Profile Authors Info & Claims Communications of the ACMVolume 43Issue 8Aug. 2000 pp 116–120https://doi.org/10.1145/345124.345164Published:01 August 2000Publication History 21citation1,420DownloadsMetricsTotal Citations21Total Downloads1,420Last 12 Months125Last 6 weeks5 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteView all FormatsPDF

The virtual interactive presenter: a conversational character for interactive television

This paper describes the development of a conversational interface for interactive TV. With the advent of multi-channel digital TV, accessing Electronic Programme Guides (EPGs) will become increasingly complex. We claim that a conversational interface can support incremental refinement of user selections, thus assisting user choice without requiring extensive knowledge of the editorial categories used in the EPG. We present the system architecture and describe the building blocks of this system in terms of underlying technologies, namely speech recognition, Natural Language Processing, dialogue modelling, character animation and multi-modal presentation. The use of an animated character appears to influence the implementation of each of these basic techniques. After giving an overview of the system behaviour and architecture, we describe the various building blocks of a conversational agent as implemented in our system and to what extent each of the underlying technologies are influenced by the use of a conversational character. We report current results by describing example dialogues from the system. Finally, we compare our approach with other interface agents' paradigms.

A plan-based agent architecture for interpreting natural language dialogue

This paper describes a plan-based agent architecture for modelling NL cooperative dialogue; in particular, the paper focuses on the interpretation of dialogue and on the explanation of its coherence by means of the recognition of the speakers' underlying intentions. The approach we propose makes it possible to analyze an explain in a uniform way several apparently unrelated linguistic phenomena, which have been often studied separately and treated via ad-hoc methods in the models of dialogue presented in the literature. Our model of linguistic interaction is based on the idea that dialogue can be seen as any other interaction among agents: therefore, domain-level and linguistic actions are treated in a similar way.Our agent architecture is based on a two-level representation of the knowledge about acting: at the metalevel, the agent modelling (AM) plans describe the recipes for plan formation and execution (they are a declarative representation of a reactive planner); at the object level, the domain and communicative actions are defined. The AM plans are used to identify the goals underlying the actions performed by an observed agent; the recognized plans constitute the dialogue context, where the intentions of all participants are stored in a structured way, in order to be used in the interpretation of the subsequent dialogue turns.

Evaluating focus theories for dialogue management

Interactive reasoning tools are usually driven by an agenda of tasks to perform, rather than by conventions of human dialogue. On the other hand, theories of dialogue in natural language tend to ignore the constraints imposed by reasoning tools. This paper presents a system composed of a reasoning module and a dialogue manager which cooperate to produce dialogues that are suitable for reasoning and follow human dialogue conventions. The dialogue manager is driven by focus rules. Various competing focus theories exist but there have been few comparative studies of their use in non-trivial tasks. We make a comparative study of the use of focus theories, which requires us to be precise about our interpretation of our chosen focus theories, and to develop an innovative means of empirical testing for them. We evaluate the theories on an example of combined dialogue and reasoning from the domain of requirements elicitation.

EditorialIntelligent Help Systems for UNIX: Planning and Knowledge Representation

This is the second of a series of three special issues on intelligent help systems for UNIX.1 This issue addresses planning and knowledge representation whereas the first issue focussed on computational models and systems and the next will be on natural language dialogue. The papers in this issue are concerned with discovering what the user wants to do, and figuring out a way to do it as well as representing the knowledge needed to do so.

Sisl: Several Interfaces, Single Logic

Modern interactive services such as information and e-commerce services are becoming increasingly more flexible in the types of user interfaces they support. These interfaces incorporate automatic speech recognition and natural language understanding and include graphical user interfaces on the desktop and web-based interfaces using applets and HTML forms. To what extent can the user interface software be decoupled from the service logic software (the code that defines the essential function of a service)? Decoupling of user interface from service logic directly impacts the flexibility of services, or how easy they are to modify and extend. To explore these issues, we have developed Sisl, an architecture and domain-specific language for designing and implementing interactive services with multiple user interfaces. A key principle underlying Sisl is that all user interfaces to a service share the same service logic. Sisl provides a clean separation between the service logic and the software for a variety of interfaces, including Java applets, HTML pages, speech-based natural language dialogue, and telephone-based voice access. Sisl uses an event-based model of services that allows service providers to support interchangeable user interfaces (or add new ones) to a single consistent source of service logic and data. As part of a collaboration between research and development, Sisl is being used to prototype a new generation of call processing services for a Lucent Technologies switching product.

EditorialIntelligent Help Systems for UNIX: Natural Language Dialogue

This is the last of a series of three special issues on intelligent help systems for UNIX.1 This issue addresses natural language dialogue whereas the previous issues focussed on computational models and systems and planning and knowledge representation, respectively. In this collection, the focus is not upon issues of parsing and production per se, even though several of the systems described here in have significant capacities in this dimension. Instead, work here has evolved more intimately within the context of consultation systems, a topic seldom dealt with by other natural language systems. Nevertheless, the issues discussed are of general concern within natural language processing.

Spracherkennung — Stand der Technik, Einsatzmöglichkeiten und Perspektiven

Automatic speech recognition and understanding has been subject to intensive research for several decades. A few years ago, the first commercial applications for the technology resulting from these efforts began to emerge. It is now obvious that speech recognition technology will soon play an important role in everyday life and also in business. In this paper, we outline the basic principles of speech recognition technology and analyze its potentials and also its limitations We discuss current and possible future applications, ranging from simple command control systems and dictation systems to natural language dialogue and translation systems.

Why machines should analyse intention in natural language dialogue

One of the most difficult problems in Artificial Intelligence (AI) is to construct a natural language processing system which can interact with users through a natural language dialogue. The problem is difficult because there are so many ways by which a user can phrase his/her utterances to such a system. An added problem is that different types of users have different types of intentions and will conduct different exchanges with the system. While many have proposed theories and models of the processing of intentions in dialogue, few of these have been incorporated within working systems and tested empirically. Here, an experiment is conducted to test what we call the Intention-Computer Hypothesis: that the analysis of intention in natural-language dialogue facilitates effective natural-language dialogue between different types of people and a computer. The experiment provides evidence to support the hypothesis. In turn, the hypothesis provides evidence for a theory of intention analysis for natural-language dialogue processing. A central principle of the theory is that coherence of natural-language dialogue can be modelled by analysing sequences of intention. A computational model, called Operating System CONsultant (OSCON), implemented in Quintus Prolog, makes use of the theory and hypothesis to understand, and answer in English, English questions about computer operating system.