Showing papers on "Chatbot published in 2009"

CSIEC: A computer assisted English learning chatbot based on textual knowledge and reasoning

Abstract: CSIEC (Computer Simulation in Educational Communication) system with newly developed multiple functions for English instruction still focuses on supplying a virtual chatting partner (chatbot), which can chat in English with the English learners anytime anywhere. It generates communicative response according to the user input, the dialogue context, the user's and its own personality knowledge, common sense knowledge, and inference knowledge. All these kinds of knowledge are expressed in the form of NLML, an annotation language for natural language text. These NLMLs can either be automatically obtained through parsing the text, or be easily authored with the help of GUI editors designed by us. So the CSIEC system suggests a naive approach of logical reasoning and inference directly through syntactical and semantic analysis of textual knowledge. This approach has advantages over the old ELIZA-like keywords matching mechanism. The chatting log summarization of free Internet usage within six months demonstrates this advantage. In this paper, we present the system architecture and underlying technologies, and the educational application results.

Deploying embodied AI into virtual worlds

Abstract: Unlike computer games where Non-Player-Character avatars are common, in most virtual worlds they are the exception. Deploying an embodied AI into a virtual world offers a unique opportunity to evaluate embodied AIs, 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.

Designing a Chatbot for diabetic patients

Abstract: Artificial Intelligence chatbot is a technology that makes interaction between man and machine possible by using natural language. In this paper, we proposed an architectural design of a chatbot that will function as virtual diabetes physician/doctor. This chatbot will allow diabetic patients to have a diabetes control/management advice without the need to go to the hospital. A general history of a chatbot, a brief description of each chatbots is discussed. We proposed the design of a new technique that will be implemented in this chatbot as the key component to function as diabetes physician. Using this design, chatbot will remember the conversation path through parameter called Vpath. Vpath will allow chatbot to gives a response that is mostly suitable for the whole conversation as it specifically designed to be a virtual diabetes physician.

Automatically Extracting Dialog Models from Conversation Transcripts

Abstract: There is a growing need for task-oriented natural language dialog systems that can interact with a user to accomplish a given objective. Recent work on building task-oriented dialog systems have emphasized the need for acquiring task-specific knowledge from un-annotated conversational data. In our work we acquire task-specific knowledge by defining \textit{sub-task} as the key unit of a task-oriented conversation. We propose an unsupervised, apriori like algorithm that extracts the sub-tasks and their valid orderings from un-annotated human-human conversations. Modeling dialogues as a combination of sub-tasks and their valid orderings easily captures the variability in conversations. It also provides us the ability to map our dialogue model to AIML constructs and therefore use off-the-shelf AIML interpreters to build task-oriented chat-bots. We conduct experiments on real world data sets to establish the effectiveness of the sub-task extraction process. We codify the extracted sub-tasks in an AIML knowledge base and build a chatbot using this knowledge base. We also show the usefulness of the chatbot in automatically handling customer requests by performing a user evaluation study.

A Semantic Layer on Semi-Structured Data Sources for Intuitive Chatbots

Abstract: The main limits of chatbot technology are related to the building of their knowledge representation and to their rigid information retrieval and dialogue capabilities, usually based on simple "pattern matching rules". The analysis of distributional properties of words in a texts corpus allows the creation of semantic spaces where represent and compare natural language elements. This space can be interpreted as a "conceptual" space where the axes represent the latent primitive concepts of the analyzed corpus.The presented work aims at exploiting the properties of a data-driven semantic/conceptual space built using semistructured data sources freely available on the web, like Wikipedia. This coding is equivalent to adding, into the Wikipedia graph, a conceptual similarity relationship layer.The chatbot can exploit this layer in order to simulate an "intuitive" behavior, attempting to retrieve semantic relations between Wikipedia resources also through associative sub-symbolic paths.

An architectural design of Virtual Dietitian (ViDi) for diabetic patients

Abstract: Artificial Intelligence chatbot is a technology that makes interaction between man and machine using natural language possible. In this paper, we proposed the architectural design of Virtual Dietition (ViDi), a chatbot that will function as virtual dietitian for diabetic patients. A general a history of a chatbot, a brief description of each chatbots is discussed. We proposed the use of new technique that will be implemented in ViDi as the key component to function as virtual dietitian. In architectural design of ViDi, Vpath is used to remember the conversation path. The architectural design will allow chatbot ViDi to response to the whole conversation as it specifically designed to be a Virtual Dietitian.

An AI Framework to Teach English as a Foreign Language: CSIEC

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-based gap filling exercises, scenario show, free chatting and chatting on a given topic—can satisfy the various requirements for students with different backgrounds and learning abilities After a brief explanation of the conception of our dialogue system, as well as a survey of related works, we will illustrate the system structure, and describe its pedagogical functions with the underlying AI techniques in detail such as NLP and rule-based reasoning We will summarize the free Internet usage within a six month period and its integration into English classes in universities and middle schools The evaluation findings about the class integration show that the chatting function has been improved and frequently utilized by the users, and the application of the CSIEC system on English instruction can motivate the learners to practice English and enhance their learning process Finally, we will conclude with potential improvements

How My Program Passed the Turing Test

Abstract: In 1989, the author put an ELIZA-like chatbot on the Internet. The conversations this program had can be seen – depending on how one defines the rules (and how seriously one takes the idea of the test itself) – as a passing of the Turing Test. This is the first time this event has been properly written. This chatbot succeeded due to profanity, relentless aggression, prurient queries about the user, and implying that they were a liar when they responded. The element of surprise was also crucial. Most chatbots exist in an environment where people expectto find some bots among the humans. Not this one. What was also novel was the onlineelement. This was certainly one of the first AI programs online. It seems to have been the first (a) AI real-time chat program, which (b) had the element of surprise, and (c) was on the Internet. We conclude with some speculation that the future of all of AI is on the Internet, and a description of the “World- Wide-Mind” project that aims to bring this about.

A Psycholinguistic Model of Man-Machine Interactions Based on Needs of Human Personality

Abstract: Fast development of internet services together with a need to automate maintains of internet services in order to reduce expenses force to use some artificial intelligence solutions that are able to interact between a man and a machine Such interactions can be carried out using internet chatbots that are able to communicate with a human in natural language supplemented with voice synthesizers A main drawback of today systems is that they do not recognize nor understand and weakly react to human needs A conversation will satisfy a human if some implemented algorithms will be able to passively recognize and classify human needs and adjust a conversation and reactions to these needs This paper describes a new personality model that can be successfully used by chatbots to achieve this goal The presented personality model figures out words, phrases and sentence constructions that can be recognized in a conversation, describes personality needs and suitable intelligent reactions to these needs in order to provide a human with satisfaction

Arabic Question-Answering via Instance Based Learning from an FAQ Corpus

Abstract: In this paper, we describe a way to access Arabic information using chatbot, without the need for sophisticated natural 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 for NL generation to recreate well-formed answers, or for deep analysis or logical inference to map user input questions onto this logical ontology; simple (but large) set of pattern-template matching rules will suffice. In previous research, this works properly with English and other European languages. In this paper, we try to see how the same chatbot will react in terms of Arabic FAQs. Initial results shows that 93% of answers were correct, but because of a lot of characteristics related to Arabic language, changing Arabic questions into other forms may lead to no answers.

Emotionally Responsive Robotic Avatars as Characters in Virtual Worlds

Abstract: This paper presents recent work on the addition of emotions and affective behaviour to robotic avatars within Second Life, as part of continuing research and development in the area of interactive agents for games and simulations. The development is based upon the E-AI architecture [1] which is a proposed computational model of emotions intended to be used by developers who already have their own agent AI systems. In this work, the E-AI architecture was applied to a currently existing commercial AI and chatbot architecture.

RMRSBot --- Using Linguistic Information to Enrich a Chatbot

Abstract: Coming to open domain dialog it is still unrealistic to implement needed knowledge resources and dialog skills linguistically. Since the Non Player Characters (NPC) in our NPC Engine should be capable of open conversation we decided to use an Artificial Intelligence Markup Language (AIML) [1] chatbot as a first workaround. However AIML chatbots are not linguistically motivated, they use surface structures in tradition of Weizenbaums ELIZA [2], wherefore they do have too many shortcomings to use them in real dialog applications. One of the major problems is the handling of surface variation. To be able to process one sentence with different structures, they need as much patterns as there are syntactic alternatives, which leads to an exploding number of pattern template pairs. To reduce the costs of the manual development, AIML authors use simple regular expression operators, what in turn leads to the problem of being overly permissive. A possibility to abstract from the surface level and still be able to control the structure is to use information from syntactic and semantic analysis. In the presented system two scenarios were implemented: 1. Using part of speech information and 2. Using the results from a semantic analysis.

An Intelligent Web-Based Human-Computer Interaction System with Natural Language CSIEC and its Integration into English Instruction

Abstract: Computer Simulation in Educational Communication (CSIEC), 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 free chatting or chatting on a given topic can satisfy the various needs from the students. This chapter will present the CSIEC system and its integration into English instruction with pilot case studies. At first the computer assisted language learning (CALL) development and research are surveyed to address the need for a virtual interactive chatting partner. Then the underlying theory and architecture of CSIEC are elucidated. This chapter mainly introduces the pedagogical functions in details and explains how to integrate the CSIEC into English class with two pilot studies in middle school, and analyzes the application and evaluation results. At last the lessons learned from the case studies and the further development direction are discussed.

Serious processing for frivolous purpose: a chatbot using web-mining supported affect analysis and pun generation

Abstract: By our demonstration we want to introduce our achievements in combining different purpose algorithms to build a chatbot which is able to keep a conversation on any topic. It uses snippets of Internet search results to stay within a context, Nakamura's Emotion Dictionary to detect an emotional load existence and categorization of a textual utterance and a causal consequences retrieval algorithm when emotive features are not found. It is also able to detect a possibility to make a pun by analyzing the input sentence and create one if timing is adequate.

A Conversational Agent to Support Decisions in SimCity like Games

Abstract: Computational intelligent techniques applied to economics have played an important role in the last years. In this paper we propose a framework based on an intelligent conversational agent embedded with a decision support system, aimed at suggesting the best managing strategies for a game-based model of a virtual town. The agent tries to prospect the future evolutions of particular choices taken by the user. Interaction is conducted through a natural language interface built as an Alice-based conversational agent.

A Web-oriented Java 3D Talking Head

Abstract: Facial animation denotes all those systems performing speech synchronization with an animated face model These kinds of systems are named Talking Heads or Talking Faces At the same time simple dialogue systems called chatbots have been developed Chatbots are software agents able to interact with users through pattern-matching based rules In this paper a Talking Head oriented to the creation of a Chatbot is presented An answer is generated in form of text triggered by an input query The answer is converted 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 exploits the naturalness of the fa cial animation and provides a real-time interactive interface to the user Besides, it is specifically suited for being used on the web This leads to a set of requirements to be satisfied, like: simple installation, visual quality, fast download, and interactivity in real time The web infrastructure has been realized using the Client-Server model The Chatbot, the Natural Language Processing and the Digital Signal Processing services are delegated to the server The client is involved in animation and synchronization This way, the server can handle multiple requests from clients The conversation module has been implemented using the ALICE (Artificial Linguistic Internet Computer Entity) technology The output of the chatbot is given input to the Natural Language Processing (Comedia Speech), incorporating a text analyzer, a letter-to-sound module and a module for the generation of prosody The client, through the synchronization module, computes the time of real duration of the animation and the duration of each phoneme and consequently of each viseme The morphing module performs the animation of the facial model and the voice reproduction As a result, the user will see the answer to question both in textual form and in the form of visual animation

Using a Chatbot to Prevent Identity Fraud By Social Engineering

Abstract: Social engineering is a threat that is expanding and threatens organisations existence. A social engineer can get hold of crucial business information that is vital for the organisation and by this threaten the organisation. To prevent successful fraud attempts the organisations need to educate their employees about social engineering fraud techniques that can be used for gaining information. Hence, information security education needs new educational approaches to cope with the threats. A solution to the problem is the use of an automated chatbot that gives the employees knowledge about a threat that is difficult to spot. To understand if an automated chatbot is a possible solution to educate the users, an investigation about the applicability is conducted. The investigation is based on a survey that compares traditional security education that is based on reading a written informational text and the use of an automated chatbot that simulates a fraud attempt with the purpose to steal an identity. The education with the automated chatbot is to be exposed to an identity fraud attempt in a controlled environment and then get an explanation of what have happened and way. The automated chatbot is developed with a fraud attempt that looks like a normal market research approach, the market research where conducted with question that gather information that is important for identity thefts. The result of the investigation shows that it may be possible to use an automated chatbot for educating in social engineering fraud attacks. However there is still a need to solve several major problems before there are possible to make sure the concept is fully feasible.

A Platform-Independent Tracking and Monitoring Toolkit.

Abstract: Issues concerning students involved with online learning paths, that need to be faced by e-Tutors on their day-to-day activity, most often than not fall into known pedagogical patterns – that are problems and difficulties already occurred in the past and dealt with. These pedagogical patterns belong to e-Tutors’ know-how and experience and their resolution are frequently a matter of activating routine processes or giving pre-factored answers; nevertheless statistical data indicates that these issues consume a considerable slice of tutors’ time. While a portion of the scientific community is still devoting much effort in developing artificial tutoring systems – by deploying AI/MAS-enabled technologies – the solution being investigated by our team focuses on enhancing alreadyavailable, open source LMS by implementing a generalpurpose tracking and monitoring toolkit able to support eTutors in recognizing and dealing with pedagogical patterns stored into a decentralised Knowledge Base. The system architecture is designed to house multiple platforms (only one adapter interface needs to be written for each LMS) and is able to perform real-time, as well as scheduled, data collection by means of Jade-based agents and schedulers. Information obtained from the processed data is then returned to the platform via web services and specific interfaces (instant messaging chatbot). The first deployed prototype is currently being experimented in adult higher education learning paths and is able to track student activity, forum readings and writings and offers a basic chat-based help interface. Our aim is to turn a standard LMS into a knowledge aggregator where information about its users, its contents and interactions between the two can be mined via Knowledge Services; resulting data could then be used to refine users’ and groups’ profiles, to monitor learners’ deviance from expected learning path, and ultimately to adjust the applied pedagogical model.

Managing Conversation Uncertainty in TutorJ

Abstract: Uncertainty in natural language dialogue is often treated through stochastic models. Some of the authors already presented TutorJ that is an Intelligent Tutoring System, whose interaction with the user is very intensive, and makes use of both dialogic and graphical modality. When managing the interaction, the system needs to cope with uncertainty due to the understanding of the user's needs and wishes. In this paper we present the extended version of TutorJ, focusing on the new features added to its chatbot module. These features allow to merge deterministic and probabilistic reasoning in dialogue management, and in writing the rules of the system's procedural memory.

Not Me: Collaboration and Co-production with Language Processing Systems

Abstract: This paper explores the use of language processing technologies for interactive artwork and studio art production. I consider text in multiple roles: as data, as index, and as a medium for interaction. After describing initial efforts with a dysfunctional chatbot, I discuss my recent work with language processing in the creation of studio art objects, and speculate about the extension of those techniques to address the large corpora of personal media we accumulate online.

An RFID Framework for Multimodal Service Provision

Abstract: In recent years there has been a growing interest toward the development of pervasive and context-aware services, and RFID technology played a relevant role in the context sensing task. We propose the use of RFID technology together with a conversational agent in order to implement a multimodal information retrieval service we call SensorMesh. The information acquired from RFID tags about the nearest point of interest is processed by the conversational agent that carries a more natural interaction with the user, also exploiting a common sense ontology. The service is accessible using a multimodal browser on Personal Digital Assistants (PDAs); the browser allows the user to interact with the conversational agent by means of spoken language instead of the traditional, keyboard- (or stylus-) based input systems. The resulting system offers a more natural interaction with respect to traditional pre-recorded, audio-visual services, and it is particularly suitable for non technology-skilled users.