Conversation with and through computers

People design what they say specifically for their conversational partners, and they adapt to their partners over the course of a conversation. A comparison of keyboard conversations involving a simulated computer partner (as in a natural language interface) with those involving a human partner (as in teleconferencing) yielded striking differences and some equally striking similarities. For instance, there were significantly fewer acknowledgments in human/computer dialogue than in human/human. However, regardless of the conversational partner, people expected connectedness across conversational turns. In addition, the style of a partner's response shaped what people subsequently typed. These results suggest some issues that need to be addressed before a natural language computer interface will be able to hold up its end of a conversation.     

一种对话机器人开发技术综述与系统架构实现

对话机器人是使用自然语言处理与生成技术,模拟人类对话逻辑并与人进行交流的计算机程序。作为新一代人工智能产品的人机交互主要入口,逻辑实现方式与交互是对话机器人设计的关键。本文结合对话机器人的技术特点,在实现过程中采用基于Python语言的Django微服务Web应用开发框架,将对话算法模型与逻辑处理过程进行微服务化API封装,使其他应用能够请求对话服务的接口进行功能的二次开发。为了提高对话响应速度,本文采用了关系型数据库MySQL与基于内存的非关系型数据库Redis结合的方式,减少算法模型对硬盘的读取次数,优化了用户体验。     

An Assessment of Written/Interactive Dialogue for Information Retrieval Applications

For the foreseeable future, natural language access to databases and other information systems will require the exchange of written messages between the system and user. Such written/interactive dialogue is unique, having the qualities of both written text and spoken discourse yet, also, differing significantly from both. In the present study, we used "Wizard of Oz" techniques to elicit written/interactive dialogue for information retrieval purposes. Our objectives in doing this were (a) to assess the general nature and prevalence of linguistic and dialogue phenomena within the written/interactive register and (b) to determine the impact of user interface shortcuts, such as precanned messages and patterned output, on both the complexity of written/interactive dialogue and general measures of user satisfaction. Our findings indicate that written/interactive dialogue for information retrieval would be very feasible. In spite of slow system response times, subjective reactions from the users were positive, the size of the lexicon used in the dialogues was small, the dialogues decomposed readily into hierarchical structures, and the number and distribution of anaphors were also rather reasonable. Two independent variables were also manipulated: (a) the degree of prefamiliarization given to participants about the base of travel information they would be accessing (i.e., the primer variable) and (b) the degree of constraint on the Wizard's ability to formulate natural language responses to the user (i.e., the natural language output variable). Failure to provide either a primer or a realistic, human natural language output made the dialogues more complex in a number of different ways.     

数据库自然语言查询界面

数据库技术的普及使得用户对数据库应用界面的要求越来越高，以往的几类接口都需要用户有较高计算机知识水平，而且必须经过一定的培训，这样就会造成人力物力的浪费而且不利于计算机的普及。本文探讨的是一种更为方便简洁不秀学习即可操作的自然语言界面。     

Route instructions in map-based human–human and human–computer dialogue: A comparative analysis

When conveying information about spatial situations and goals, speakers adapt flexibly to their addressee in order to reach the communicative goal efficiently and effortlessly. Our aim is to equip a dialogue system with the abilities required for such a natural, adaptive dialogue. In this paper we investigate the strategies people use to convey route information in relation to a map by presenting two parallel studies involving human–human and human–computer interaction. We compare the instructions given to a human interaction partner with those given to a dialogue system which reacts by basic verbal responses and dynamic visualization of the route in the map. The language produced by human route givers is analyzed with respect to a range of communicative as well as cognitively crucial features, particularly perspective choice and references to locations across levels of granularity. Results reveal that speakers produce systematically different instructions with respect to these features, depending on the nature of the interaction partner, human or dialogue system. Our further analysis of clarification and reference resolution strategies produced by human route followers provides insights into dialogue strategies that future systems should be equipped with.     

A form-based natural language front-end to a CIM database

The paper presents a methodology for developing a user interface that combines fourth generation interface tools (SQL forms) with a natural language processor for a database management system. The natural language processor consists of an index, a lexicon and a parser. The index is used to uniquely identify each form in the system through a conceptual representation of its purpose. The form fields specify database or nondatabase fields whose values are either entered by the user (user-defined) or are derived by the form (system-defined) in response to user input. A set of grammar rules are associated with each form. The lexicon consists of all words recognized by the system, their grammatical categories, roots, their associations (if any) with database objects and forms. The parser scans, a natural language query to identify a form in a bottom-up fashion. The information requested in the user query is determined in a top-down manner by parsing, through the grammar rules associated with the identified form. Extragrammatical inputs with limited deviations from the grammar rules are supported. Combining a natural language processor with SQL forms allows processing data modification tasks without violating any database integrity constraint, having duplicate records, or entering invalid data. A prototype natural language interface is described as a front-end to an ORACLE database for a computer integrated manufacturing system     

MeteoBayes: Effective Plan Recognition in a Weather Dialogue System

When you've called a voice portal for any kind of information retrieval, chances are that an automated system guided the entire interaction. It might have correctly identified your goal, but probably only after asking too many questions. MeteoBayes is a meteorological information dialogue system that lets you use natural language to direct the interaction. Based on Bayesian networks, MeteoBayes' inference engine attempts to identify user intentions by consulting its past dialogue repository. For unfamiliar words, MeteoBayes has an unknown-term disambiguation module that learns word similarities from texts to avoid unnecessary system inquiries, thus speeding up the understanding process     

数据库驱动的对话机器人技术实现

世界上很多高价值的数据信息储存在关系数据库中,访问这些数据需要掌握专门的结构化查询语言(SQL),普通人很难直接使用。基于对现有对话机器人存在的问题和相关关键技术的梳理,本文融合了数据仓库、数据同步、数据库查询、消息推送、自然语言理解及语音识别等相关技术及产品,设计了数据库驱动的对话机器人。方案可以实现用户理解、消息推送、事实数据查询和分析数据查询四个功能,使得用户能够快速地获取信息。本文提出的数据库驱动的对话机器人具有较强的泛化性和可扩展性。     

Josef,the robot

Computers cannot be properly understood without at least an elementary exposure to programming. Many teachers would reject this proposal on the grounds that for many people programming is too difficult and uninteresting. This objection is probably correct if we imply that programming should be introduced in a general purpose programming language. Its validity becomes questionable if the vehicle is a special programming language which puts the student into a natural environment, familiar to every ordinary person.The LOGO system is a well known example of such a natural environment. This article presents a related language called Josef which is used to program a robot moving on the map of a computer terminal. The distinguishing features of Josef are: (a) Extensibility of built-in vocabulary: (b) Possibility of fully top-down approach to the solution of large problems; (c) Similarity to general purpose languages in terms of concepts available in the language and the syntax used to express them: (d) Ability to work on ordinary computer terminals.The larger part of the article attempts to present the general philosophy of the language on a few programming examples of medium complexity.     

Evaluation of Methods for the Determination of Factors Inducing Fatigue in Man at Work

The aim of the study was to determine the influence of textual feedback on the content and outcome of spoken interaction with a natural language dialogue system. More specifically, the assumption that textual feedback could disrupt spoken interaction was tested in a human–computer dialogue situation. In total, 48 adult participants, familiar with the system, had to find restaurants based on simple or difficult scenarios using a real natural language service system in a speech-only (phone), speech plus textual dialogue history (multimodal) or text-only (web) modality. The linguistic contents of the dialogues differed as a function of modality, but were similar whether the textual feedback was included in the spoken condition or not. These results add to burgeoning research efforts on multimodal feedback, in suggesting that textual feedback may have little or no detrimental effect on information searching with a real system.

Statement of Relevance: The results suggest that adding textual feedback to interfaces for human–computer dialogue could enhance spoken interaction rather than create interference. The literature currently suggests that adding textual feedback to tasks that depend on the visual sense benefits human–computer interaction. The addition of textual output when the spoken modality is heavily taxed by the task was investigated.     

Multimodal Interaction for Information Access: Exploiting Cohesion

Multimodality is a powerful concept for dealing with dialogue cohesion in a human–computer natural language (NL)‐centered system. This work is a modest step toward more effective exploitation of the potentially large bandwidth of communication provided by this situation. The relations between exploration, navigation, and NL‐based communication are discussed in general and with reference to two prototypes. Light cognitive load feedback and direct manipulation are proposed so that user and system can cooperate in mutually establishing the structure of the ongoing dialogue. The main points are: (i) use of an appropriate dialogue structure to constrain inference in the anaphora resolution process; (ii) use of a graphical representation of the structure, to limit the problem of opacity; (iii) allowance for the possibility of direct manipulation on this representation, to avoid the necessity of operating linguistically at the metalevel. The context of the work is within NL‐centered multimodal information access systems, in which basic entities are pairs (most commonly question and answer). A dialogue model is provided by a modified version of the centering model; it is both sufficiently simple to be displayed in an intuitive fashion on the screen, and sufficiently powerful to give accurate results. An extension of the discourse model, oriented to the treatment of deixis, is also proposed. Finally, steps toward an overall approach to the integration of navigational and mediated aspects of interaction are discussed.     

An expert intermediary system for interactive document retrieval

Constructing natural language interfaces to computer systems often requires achievement of advanced reasoning and expert capabilities in addition to basic natural language understanding. In this paper the above issue is tackled in the frame of an actual application concerning the design of a natural language interface for interactive document retrieval. After a short discussion of the peculiarities of this application, which requires both natural language understanding and reasoning capabilities, the general architecture and fundamental design criteria of a system presently being developed at the University of Udine are presented. The system, named IR-NLI, is aimed at allowing non-technical users to directly access through natural language the services offered by online databases. Attention is later focused on the basic functions of IR-NLI, namely understanding, dialogue and reasoning. An example of interaction with IR-NLI is fully worked out to introduce the main features of the system. Knowledge representation methods and algorithms adopted are then illustrated. Perspectives and direction for future research are also discussed.     

Using speech and dialogue for interactive TV navigation

Interaction techniques for interactive television (iTV) are currently complex and difficult to use for a wide-range of viewers. Few previous studies have dealt with the potential benefits of multimodal dialogue interaction in the context of iTV for the purpose of flexibility, usability, efficiency, and accessibility. This paper investigates the benefits of introducing speech and connected dialogue for iTV interaction, and presents a case study in which a prototype system was built allowing users to navigate the information space and control the operation of the TV by a speech-based natural language interface. The system was evaluated by analysing the user experience in five categories capturing essential aspects of iTV interaction: interaction style, information load, data access, effectiveness and initiative. Design considerations relevant for speech and dialogue information systems for TV interfaces also emerged from the analysis.     

面向任务的基于深度学习的多轮对话系统与技术

自然语言是人类智慧的结晶,以自然语言的形式与计算机进行交互是人们长久以来的期待。随着自然语言处理技术的发展与深度学习方法的兴起,人机对话系统成为了新的研究热点。人机对话系统按照功能可以分为任务导向型对话系统、闲聊型对话系统、问答型对话系统。任务导向型对话系统是一种典型的人机对话系统,旨在帮助用户完成某些特定的任务,有着十分重要的学术意义和应用价值。文中系统地阐述了一种在实际工程应用中的任务导向型对话系统的通用框架,主要包括自然语言理解、对话管理以及自然语言生成3个部分;介绍了上述各部分所采用的经典深度学习和机器学习方法。最后,对自然语言理解任务进行了实证性的实验验证与分析,结果表明文中内容可以为任务导向型对话系统的构建提供有效指导。     

Dialogue patterns—A visual language for dynamic dialogue

A dynamic dialogue is a conversation in which each participant alternately selects remarks based on a changing world state and in which each remark can change the world state. Dynamic dialogues happen frequently as conversations between a player character (PC) and a non-player character (NPC) in a computer game. When it is the PC's turn to speak, the current game state is used to filter the static set of remarks available to the PC to a contextually appropriate subset that is made available to the player. Selecting a PC remark then leads to a candidate set of NPC remarks as appropriate responses to the PC. The world state is used to filter this set of remarks to a single remark, which is used by the NPC as the reply. To construct a dynamic dialogue, an author must not only create the remarks, but also write the code that determines which remarks are available to both participants at any point in the dialogue. We present “generative dialogue patterns” as a new visual language for designing dynamic dialogues and generating the program code that is necessary to select the appropriate remarks during the dialogue. We use a case study from the computer games domain to evaluate the effectiveness of generative dialogue patterns.     

Using a natural language interface with casual users

Although there is much controversy about the merits of natural language interfaces, little empirical research has been conducted on the use of natural language interfaces for database access, especially for casual users. In this work casual users were observed while interacting with a real-life database using a natural language interface, Intellect.Results show that natural language is an efficient and powerful means for expressing requests. This is especially true for users with a good knowledge of the database contents regardless of training or previous experience with computers. Users generally have a positive attitude towards natural language. The majority of errors users make are directly related to restrictions in the vocabulary. However, feedback helps users understand the language limitations and learn how to avoid or recover from errors. Natural language processing technology is developed enough to handle the limited domain of discourse associated with a database; it is simple enough to support casual users with a general knowledge of the database contents; and it is flexible enough to assist problem-solving behaviour.     

Approaches to natural language discourse processing

One of the most difficult problems within the field of Artificial Intelligence (AI) is that of processing language by computer, or natural-language processing. A major problem in natural-language processing is to build theories and models of how individual utterances cling together into a coherent discourse. The problem is important because, to properly understand natural language, a computer should have some sense of what it means for a discourse to be coherent and rational. Theories, models and implementations of natural-language processing argue for a measure of coherence based on three themes: meaning, structure, and intention. Most approaches stress one theme over all the others. Their future lies in the integration of components of all approaches. A theory of intention analysis solves, in part, the problem of 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. The theory of intention analysis has been incorporated within a computational model, called Operating System CONsultant (OSCON), implemented in Quintus Prolog, which understands, and answers in English, English questions about computer operating systems. Theories and implementations of discourse processing will not only enable people to communicate better with computers, but also enable computers to better communicate with people.