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Showing papers on "Chatbot published in 2008"


Journal ArticleDOI
TL;DR: A conversational agent, or ''chatbot'' has been developed to allow the learner to negotiate over the representations held about them using natural language, to support the metacognitive goals of self-assessment and reflection, which are increasingly seen as key to learning and are being incorporated into UK educational policy.
Abstract: This paper describes a system which incorporates natural language technologies, database manipulation and educational theories in order to offer learners a Negotiated Learner Model, for integration into an Intelligent Tutoring System. The system presents the learner with their learner model, offering them the opportunity to compare their own beliefs regarding their capabilities with those inferred by the system. A conversational agent, or ''chatbot'' has been developed to allow the learner to negotiate over the representations held about them using natural language. The system aims to support the metacognitive goals of self-assessment and reflection, which are increasingly seen as key to learning and are being incorporated into UK educational policy. The paper describes the design of the system, and reports a user trial, in which the chatbot was found to support users in increasing the accuracy of their self-assessments, and in reducing the number of discrepancies between system and user beliefs in the learner model. Some lessons learned in the development have been highlighted and future research and experimentation directions are outlined.

118 citations


Journal ArticleDOI
01 Jan 2008-ReCALL
TL;DR: It is concluded that while substantial progress has been made in terms of chatbots' language-handling, a robust ESL ‘conversation practice machine’ is still some way off being a reality.
Abstract: This paper investigates the linguistic worth of current ‘chatbot’ programs – software programs which attempt to hold a conversation, or interact, in English – as a precursor to their potential as an ESL (English as a second language) learning resource. After some initial background to the development of chatbots, and a discussion of the Loebner Prize Contest for the most ‘human’ chatbot (the ‘Turing Test’), the paper describes an in-depth study evaluating the linguistic accuracy of a number of chatbots available online. Since the ultimate purpose of the current study concerns chatbots' potential with ESL learners, the analysis of language embraces not only an examination of features of language from a native-speaker's perspective (the focus of the Turing Test), but also aspects of language from a second-language-user's perspective. Analyses indicate that while the winner of the 2005 Loebner Prize is the most able chatbot linguistically, it may not necessarily be the chatbot most suited to ESL learners. The paper concludes that while substantial progress has been made in terms of chatbots' language-handling, a robust ESL ‘conversation practice machine’ (Atwell, 1999) is still some way off being a reality.

53 citations


Proceedings ArticleDOI
18 Oct 2008
TL;DR: Automatic chatbot knowledge acquisition method from online forums is presented, which includes a classification model based on rough set and the theory of ensemble learning is combined to make a decision.
Abstract: Existing chatbot knowledge bases are mostly hand-constructed, which is time consuming and difficult to adapt to new domains. Automatic chatbot knowledge acquisition method from online forums is presented in this paper. It includes a classification model based on rough set, and the theory of ensemble learning is combined to make a decision. Given a forum, multiple rough set classifiers are constructed and trained first. Then all replies are classified with these classifiers. The final recognition results are drawn by voting to the output of these classifiers. Finally, the related replies are selected as chatbot knowledge. Relevant experiments on a child-care forum prove that the method based on rough set has high recognition efficiency to related replies and the combination of ensemble learning improves the results.

26 citations


Proceedings ArticleDOI
19 Jun 2008
TL;DR: A layered management architecture that mixes task-oriented dialogue techniques with chatbot techniques to achieve better persuasiveness in the dialogue is introduced.
Abstract: Argumentation is an emerging topic in the field of human computer dialogue. In this paper we describe a novel approach to dialogue management that has been developed to achieve persuasion using a textual argumentation dialogue system. The paper introduces a layered management architecture that mixes task-oriented dialogue techniques with chatbot techniques to achieve better persuasiveness in the dialogue.

19 citations


Proceedings ArticleDOI
04 Mar 2008
TL;DR: The Graphical Artificial Intelligence Markup Language is presented, an extension of AIML allowing merging of verbal and graphical interaction modalities and a chatbot system, Graphbot, is also presented that is able to support this language.
Abstract: One of the aims of the research in the field of the human-computer interaction is the design of a natural and intuitive interaction modalities In particular, many efforts have been devoted in the development of systems able to interact with the user in natural language Chatbots are the classical interfaces for natural language interaction Such systems can be very sophisticated, including support for 3D avatars and speech analysis and synthesis However, all of them present only a text area allowing the user to input her sentences No doubt, an interaction involving also the natural language can increase the comfort of the user with respect to common interfaces using only graphical widgets However, multi-modal communication must be preferred in all those situations when the user and the system have a tight interaction Typical examples are cultural heritages applications (intelligent museum guides, picture browsing) or systems presenting to the user an information integrated from different sources as in the case of the iGoogle (TM) interface In this work we present the Graphical Artificial Intelligence Markup Language, an extension of AIML allowing merging of verbal and graphical interaction modalities A chatbot system, Graphbot, is also presented that is able to support this language The language is able to define personalized interface patterns that are the most suitable ones in relation to the type of data exchanged between the user and the system during the dialogue

16 citations


Book ChapterDOI
25 Jun 2008
TL;DR: The summarization and assessment findings confirm that the chatting function has been enhanced and fully used by the users, and the application of the CSIEC system in English instruction can interest the learners to study English and motivate them to practice English more frequently.
Abstract: CSIEC (Computer Simulation in Educational Communication), is an interactive web-based human-computer dialogue system with natural language for English instruction In this paper we present its newest developments and applications in English education After brief introduction of the project motivation and the related works, we illustrate the system structure with a flow diagram, and describe its pedagogical functions in details, including free chatting, chatting on a given topic and the chatting scoring mechanism We review the free Internet usage within six months, and evaluate its integration into English classroom The summarization and assessment findings confirm that the chatting function has been enhanced and fully used by the users, and the application of the CSIEC system in English instruction can interest the learners to study English and motivate them to practice English more frequently Finally we discuss the application driven approach of system development, and draw some conclusions for the further improvements

15 citations


Book ChapterDOI
23 Jun 2008
TL;DR: A case study of the integration of CSIEC's multiple functions into English syllabus design in a middle school and its pedagogical effectiveness and the survey data indicates the students' favor to this system.
Abstract: CSIEC (Computer Simulation in Educational Communication), is not only an intelligent web-based human-computer dialogue system with natural language for English instruction, but also a learning assessment system for learners and teachers. Its multiple functions including grammar gap filling exercises, talk show and chatting on a given topic, can satisfy the various needs from the students with different backgrounds and learning abilities. In this paper we present a case study of the integration of CSIEC's multiple functions into English syllabus design in a middle school and its pedagogical effectiveness. The comparison of two examination results before and after the system integration shows great improvement of students' performance, and the survey data also indicates the students' favor to this system.

14 citations


Journal ArticleDOI
TL;DR: In this paper, the potential of chatbots for ESL (English as a Second Language) learning from a pedagogical perspective is explored, and six chatbots are evaluated from the perspective of their interfaces as a human-looking or sounding partner to chat with.
Abstract: 'Chatbot' programs are pieces of software that can hold a conversation, or interact, in English. This paper explores the potential of chatbots for ESL (English as a Second Language) learning from a pedagogical perspective. From the command-line days of Eliza, chatbots have matured considerably – to the point where many chatbots now involve an avatar interface, with speech recognition also becoming available as a feature. The paper evaluates six chatbots currently available either online or for purchase. The evaluation examines chatbots from the perspective of their interfaces as a human-looking or sounding partner to chat with, as well as their usability as pieces of software suitable for ESL learners. To put some of these issues in perspective and provide insights into their use, the paper also reports on the use of some chatbots in the ESL classroom. The paper concludes with an analysis of chatbots currently available, noting that while chatbots have matured considerably since the early days of Eliza, they still have a long way to go before they can interact with students in the way that researchers such as Atwell (1999) envisage.

11 citations


DOI
01 Jan 2008
TL;DR: Findings showed that users’ sensory, emotional, cultural, linguistic and relational engagement influenced their responses to the chatbot interface, which in turn, shaped their learning processes.
Abstract: During the past few decades, there has been increasing attention to multimodal adaptive language learning interface design. The purpose of this study was to examine users’ experiences with a chatbot language learning interface through the lens of cognitive emotions and emotions in learning. A particular focus of this study was on users’ interactions with a chatbot in a public setting and in a private environment. Focusing on the event of users’ interaction with a chatbot interface, seventy-five interactions were videotaped in this study, in which fifteen users were asked to interact with the chatbot “Lucy” for their language learning. The video-stimulated post interaction interviews with participants provided complementary data for understanding their experiences with the language learning system. Analysis of twenty-five interactions selected from a total of seventy-five revealed five main factors of chatbot language tutor interface design and their relative significance in the process of users’ meaning making and knowledge construction. Findings showed that users’ sensory, emotional, cultural, linguistic and relational engagement influenced their responses to the chatbot interface, which in turn, shaped their learning processes. Building on a theoretical framework of cognitive emotions and emotions in learning, this study documented users’ language learning processes with the chatbot language learning interface by investigating users’ experiences. The findings and techniques resulting from this study will help designers and researchers achieve a better understanding of users’ experiences with technology and the role of emotions in the processes of learning when using technology and assist them to improve the design of language learning environments.

10 citations


Journal ArticleDOI
TL;DR: The result of this proposal is the Graphical Artificial Intelligence Markup Language (GAIML) an extension of AIML allowing merging both interaction modalities to build systems with a reconfigurable interface, which is able to change with respect to the particular application context.
Abstract: Natural and intuitive interaction between users and complex systems is a crucial research topic in human-computer interaction. A major direction is the definition and implementation of systems with natural language understanding capabilities. The interaction in natural language is often performed by means of systems called chatbots. A chatbot is a conversational agent with a proper knowledge base able to interact with users. Chatbots appearance can be very sophisticated with 3D avatars and speech processing modules. However the interaction between the system and the user is only performed through textual areas for inputs and replies. An interaction able to add to natural language also graphical widgets could be more effective. On the other side, a graphical interaction involving also the natural language can increase the comfort of the user instead of using only graphical widgets. In many applications multi-modal communication must be preferred when the user and the system have a tight and complex interaction. Typical examples are cultural heritages applications (intelligent museum guides, picture browsing) or systems providing the user with integrated information taken from different and heterogenous sources as in the case of the iGoogle™ interface. We propose to mix the two modalities (verbal and graphical) to build systems with a reconfigurable interface, which is able to change with respect to the particular application context. The result of this proposal is the Graphical Artificial Intelligence Markup Language (GAIML) an extension of AIML allowing merging both interaction modalities. In this context a suitable chatbot system called Graphbot is presented to support this language. With this language is possible to define personalized interface patterns that are the most suitable ones in relation to the data types exchanged between the user and the system according to the context of the dialogue.

9 citations


01 Jan 2008
TL;DR: A way to access informati on using chatbot, without the need for sophisticated n atural language processing or logical inference, is described, which does not require the sophisticated analysis techniques.
Abstract: In this paper we describe a way to access informati on using chatbot, without the need for sophisticated n atural language processing or logical inference. FAQs are Frequently-Asked Questions documents, designed to capture the logical ontology of a given domain. Any Natural Language interface to an FAQ is constrained to reply with the given Answers, so there is no need f or NL generation to recreate well-formed answers, or for deep analysis or logical inference to map user input que stions onto this logical ontology; simple (but large) set of pattern-template matching rules will suffice. In th is paper and as an evidence for this argument, the FAQ in th e School of Computing (SoC) at the University of Leed s as well as Perl, Linux, and Python were used to retrai n the ALICE chat-bot system, producing FAQchat. The repli es from FAQchat looks like results generated by WWW search engines such as AskJeeves or Google. User tr ials with AskJeeves, Google and FAQchat demonstrate that FAQchat is a viable alternative, and in fact many u sers prefer it to Google as tool to access FAQ databases . The restricted domain of an FAQ is special case of Ques tionAnswering which does not require the sophisticated analysis techniques.

Proceedings ArticleDOI
25 May 2008
TL;DR: A talking head is system performing an animated face model synchronized with a speech synthesis module used as a presentation layer of a conversational agent which provide an answer when a query is written as an input by the user.
Abstract: A talking head is system performing an animated face model synchronized with a speech synthesis module. It is used as a presentation layer of a conversational agent which provide an answer. It provides an answer when a query is written as an input by the user. The textual answer is converted into facial movements of a 3D face model whose lips and tongue movements are synchronized with the sound of the synthetic voice. The client-server paradigm has been used for the WEB infrastructure delegating the animation and synchronization to the client, so that the server can satisfy multiple requests from clients; while the Chatbot, the digital signal processing and the natural language processing are provided by the server.

Journal ArticleDOI
TL;DR: This is an exploratory study that reviews five randomly chosen conversations that an animated chatbot has with Web users, where the character simulates human gestures, but they are stylized to reproduce animation standards.
Abstract: Conversational agents that display many human qualities have become a valuable method business uses to communicate with online users to supply services or products, to help in online order process or to search the Web. The gaming industry and education may benefit from this type of interface. In this type of chats, users could have different alternatives: text display, photo of a real person, or a cartoon drawing and others. This is an exploratory study that reviews five randomly chosen conversations that an animated chatbot has with Web users. The character simulates human gestures, but they are stylized to reproduce animation standards. The goal of this exploratory study is to provide feedback that will help designers to improve the functionality of the conversational agent, identify user’s needs, define future research, and learn from previous errors. The methodology used was qualitative content analysis

Book ChapterDOI
09 Dec 2008
TL;DR: An architecture being used for the deployment of chatbot driven avatars within the Second Life virtual world is presented, the challenges of deploying an AI within such a virtual world, the possible implications for the Turing Test are looked at, and research directions for the future are identified.
Abstract: The last two years have seen the start of commercial activity within virtual worlds. Unlike computer games where Non-Player-Character avatars are common, in most virtual worlds they are the exception — and until recently in Second Life they were non-existent. However there is real commercial scope for Als in these worlds — in roles from virtual sales staff and tutors to personal assistants. Deploying an embodied AI into a virtual world offers a unique opportunity to evaluate embodied Als, and to develop them within an environment where human and computer are on almost equal terms. This paper presents an architecture being used for the deployment of chatbot driven avatars within the Second Life virtual world, looks at the challenges of deploying an AI within such a virtual world, the possible implications for the Turing Test, and identifies research directions for the future.

Proceedings ArticleDOI
06 Oct 2008
TL;DR: An evaluation was conducted to determine whether a natural language interface would provide a more effective automation technique in comparison to current techniques utilised by contact centres and concluded that a hybrid system utilising a combination of these techniqueswould provide a better solution.
Abstract: The usability of touch-tone Interactive Voice Response (IVR) systems is dismal. Clients would rather speak to a contact centre agent than navigate through the menu structure found in these systems. Contact centres, due to a variety of reasons, most notably high personnel costs, tend to utilise IVR as their solution for automation. IVR is an example of a simple forward chaining rule based expert system. An evaluation was conducted to determine whether a natural language interface would provide a more effective automation technique in comparison to current techniques utilised by contact centres. This evaluation compared the advantages and disadvantages of a natural language interface and a rule based expert system interface (modelled to resemble an IVR) and concluded that a hybrid system utilising a combination of these techniques would provide a better solution. This paper discusses two models that could be employed in the combination of a rule based expert system with a natural language interface.

06 Oct 2008
TL;DR: Observations on listening behaviour research and one of the applications, the virtual diary companion, is introduced, which requires a more patient or relaxed attitude, waiting for the right moment to provide feedback to the human partner.
Abstract: Chatbots and embodied conversational agents show turn based conversation behaviour. In current research we almost always assume that each utterance of a human conversational partner should be followed by an intelligent and/or empathetic reaction of chatbot or embodied agent. They are assumed to be alert, trying to please the user. There are other applications which have not yet received much attention and which require a more patient or relaxed attitude, waiting for the right moment to provide feedback to the human partner. Being able and willing to listen is one of the conditions for being successful. In this paper we have some observations on listening behaviour research and introduce one of our applications, the virtual diary companion.

Proceedings ArticleDOI
04 Mar 2008
TL;DR: This paper's "talking head" explores the naturalness of the facial animation and provides a real-time interactive interface to the user and delegating the Chatbot, the natural language processing and the digital signal processing services to the server while the client is involved in animation, synchronization.
Abstract: Facial animation is referred to all those systems performing the speech synchronization with an animated face model. This kind of systems are called "talking head" or "talking face". In this paper a Talking Head oriented to the creation of a Chatbot is presented. It requires an input query and an answer is generated in form of text. The answer is transduced into a facial animation using a 3D face model whose lips movements are synchronized with the sound produced by a speech synthesis module. Our "talking head" explores the naturalness of the facial animation and provides a real-time interactive interface to the user. The Web infrastructure has been realized using the client-server model delegating the Chatbot, the natural language processing and the digital signal processing services to the server, while the client is involved in animation, synchronization; in this way, the server can handle multiple requests from clients.