自然语言生成综述

自然语言生成(NLG)技术利用人工智能和语言学的方法来自动地生成可理解的自然语言文本.NLG降低了人类和计算机之间沟通的难度,被广泛应用于机器新闻写作、聊天机器人等领域,已经成为人工智能的研究热点之一.首先,列举了当前主流的NLG的方法和模型,并详细对比了这些方法和模型的优缺点;然后,分别针对文本到文本、数据到文本和图...     

Lexicalization in natural language generation: A survey

In natural language generation, a meaning representation of some kind is successively transformed into a sentence or a text. Naturally, a central subtask of this problem is the choice of words, orlexicalization. In this paper, we propose four major issues that determine how a generator tackles lexicalization, and survey the contributions that researchers have made to them. Open problems are identified, and a possible direction for future research is sketched.     

Creating natural language interfaces to VR systems

Two research projects are described that explore the use of spoken natural language interfaces to virtual reality (VR) systems. Both projects combine off-the-shelf speech recognition and synthesis technology with in-house command interpreters that interface to the VR applications. Details about the interpreters and other technical aspects of the projects are provided, together with a discussion of some of the design decisions involved in the creation of speech interfaces. Questions and issues raised by the projects are presented as inspiration for future work. These issues include: requirements for object and information representation in VR models to support natural language interfaces; use of the visual context to establish the interaction context; difficulties with referencing events in the virtual world; and problems related to the usability of speech and natural language interfaces in general.     

Enhancing information systems management with natural language processing techniques

Natural language and databases are core components of information systems. They are related to each other because they share the same purpose: the conceptualization aspects of the real world in order to deal with them in some way. Natural language processing (NLP) techniques may substantially enhance most phases of the information system lifecycle, starting with requirements analysis, specification and validation, and going up to conflict resolution, result processing and presentation. Furthermore, natural language based query languages and user interfaces facilitate the access to information for anyone and allow for new paradigms in the usage of computerized services. This paper investigates the use of NLP techniques in the design phase of information systems. Then, it reports on data base querying and information retrieval enhanced with NLP.     

Computer animated visual translation from natural language to sign language

Computer animation and visualization can facilitate communication between the hearing impaired and those with normal speaking capabilities. This paper presents a model of a system that is capable of translating text from a natural language into animated sign language. Techniques have been developed to analyse language and transform it into sign language in a systematic way. A hand motion coding method as applied to the hand motion representation, and control has also been investigated. Two translation examples are also given to demonstrate the practicality of the system.     

基于自然语言生成的关联规则可视化方法

针对传统的关联规则蕴含式表示方式和图形可视化方法对非专家用户来说不易理解的问题,提出了一种新的基于自然语言生成的关联规则可视化方法。该方法将自然语言生成技术引入到关联规则可视化中,通过领域知识库中的解释模式将关联规则中每一项生成简单的自然语言句子,并经过句子规划、表层实现,最终生成流畅的自然语言句子。实验最终得出的结果,便于普通用户理解和应用,从而帮助用户获取更有价值的信息。     

Net generation students: agency and choice and the new technologies

Based on research investigating English first‐year university students, this paper examined the case made for a new generation of young learners often described as the Net Generation or Digital Natives in terms of agency and choice. Generational arguments set out a case that links young people's attitudes and orientations to their lifelong exposure to networked and digital technologies. This paper drew on interview data from mixed methods research to suggest that the picture is more complex than the equation of exposure to new technologies and a generational change of attitudes and capacities. Starting from the position that interaction with technology is mediated by activity and an intentional stance, we examined the choices students make with regard to the technologies they engage with. We explored the perceived constraints students face and the way they either comply or resist such constraints. We concluded that agency actively shapes student engagement with technology but that an adequate conception of agency must expand beyond the person and the self to include notions of collective agency identifying the meso level as an activity system that mediates between the students and their technological setting.     

Reversible logic grammars for natural language parsing and generation

The use of a single grammar in natural language parsing and generation is most desirable for a variety of reasons, including efficiency, perspicuity, integrity, robustness, and a certain amount of elegance. These characteristics have been noted before by several researchers, but it was only recently that more serious attention started to be paid to the problem of creating a bidirectional system for natural language processing. In this paper we discuss a somewhat more radical version of the problem: given a parser for a language, can we reverse it so that it becomes an efficient generator for the same language? Furthermore, since both the parser and the generator are based upon the same grammar, are there any normalization conditions upon the form of the grammar that must be met in order to assure the maximum efficiency of the reversed program? Can other grammars be transformed into the normal form? We describe the results of an experiment with PROLOG-based logic grammar which has been derived from a substantial-coverage string grammar for English. We present an alogorithm for automated inversion of a unification parser into an efficient unification generator, using the collections of minimal sets of essential arguments for predicates. We discuss the scope of the present version of the algorithm and then point out several possible avenues for extension. We also outline a preliminary solution to the question of grammar's “normal form” and suggest a handful of normalizing transformations that can be used to enhance the efficiency of the generator. This research interacts closely with a Japanese-English machine translation project at New York University, for which the first implementation of the inversion algorithm has been prepared.     

Natural language generation and deep learning for intelligent building codes

Many existing automated compliance checking (ACC) systems require the processes of extracting regulatory information from natural-language building-code requirements and transforming the extracted information into computer-processable semantic representations. These processes could, however, be jeopardized by the ambiguous nature of the natural language and the hierarchically complex structures of building-code requirements. To address this problem, this paper proposes the concept of intelligent building code for bypassing the error-prone information extraction and transformation processes. In the proposed intelligent code, the natural-language requirements in the code are connected with highly structured computer-understandable semantic information, which is represented in the form of semantic requirement hierarchies and can be readily used by computers for ACC. The paper also proposes a deep learning-based method to automatically generate such intelligent code. The method leverages the requirement hierarchy representation, a proposed deep learning unit-to-text model for generating requirement sentence segments, and a proposed semantic correspondence score for configuring the segments into requirement sentences. The method was implemented and tested on a dataset from multiple regulatory documents. The generated intelligent requirements were evaluated in terms of both natural-language requirement comprehensibility and correspondence between the natural language and the semantic representation, with the results indicating high performance for the proposed representation and method. The proposed intelligent code will help reduce ACC errors, improve requirement comprehensibility, and facilitate intelligent code analytics.     

Analysing and evaluating the task of automatic tweet generation: Knowledge to business

In this paper a study concerning the evaluation and analysis of natural language tweets is presented. Based on our experience in text summarisation, we carry out a deep analysis on user's perception through the evaluation of tweets manual and automatically generated from news. Specifically, we consider two key issues of a tweet: its informativeness and its interestingness. Therefore, we analyse: (1) do users equally perceive manual and automatic tweets?; (2) what linguistic features a good tweet may have to be interesting, as well as informative? The main challenge of this proposal is the analysis of tweets to help companies in their positioning and reputation on the Web. Our results show that: (1) automatically informative and interesting natural language tweets can be generated as a result of summarisation approaches; and (2) we can characterise good and bad tweets based on specific linguistic features not present in other types of tweets.     

Spatial representation of context-dependent sentences and its application to sentence generation

We propose a novel approach to embedding sentences into a high-dimensional space. Independent words in the sentence are located at points in the space, and the sentence is represented by a curve along these words. A set of functions that evaluates a sequence of words is designed over this space and is helpful for searching for words that are likely to follow the observed sentences. More generally, our approach makes sentences sequentially depending on the context. We simplify Japanese grammar and subsequently implement it as a grammar that constrains simple sentences to be generated. In this study, we performed experiments in which we created a dictionary containing 2877 different independent words and constructed a semantic space from texts in eight digital archived books, consisting of 8495 independent words and 161 paragraphs in total. It was demonstrated that several meaningful sentences can be generated that are likely to follow untrained input sentences.     

Evaluating the usability of natural language query languages and interfaces to Semantic Web knowledge bases

The need to make the contents of the Semantic Web accessible to end-users becomes increasingly pressing as the amount of information stored in ontology-based knowledge bases steadily increases. Natural language interfaces (NLIs) provide a familiar and convenient means of query access to Semantic Web data for casual end-users. While several studies have shown that NLIs can achieve high retrieval performance as well as domain independence, this paper focuses on usability and investigates if NLIs and natural language query languages are useful from an end-user's point of view. To that end, we introduce four interfaces each allowing a different query language and present a usability study benchmarking these interfaces. The results of the study reveal a clear preference for full natural language query sentences with a limited set of sentence beginnings over keywords or formal query languages. NLIs to ontology-based knowledge bases can, therefore, be considered to be useful for casual or occasional end-users. As such, the overarching contribution is one step towards the theoretical vision of the Semantic Web becoming reality.     

Combining natural language with direct manipulation: the conceptual framework for a hybrid human-computer interface

This paper describes the development of a conceptual model of an interaction system for future human-computer interaction. It is suggested that an integrated system is the most promising solution for diverse users and tasks. A ' hybrid interaction system' is considered, which tries to efficiently direct manipulation, menu selection, and natural language. The mechanism of the natural language interface module is described in more detail. Finally, the allocation of functionalities for generalized tasks on the conceptual model is considered from the taxonomic approach.     

Combining natural language with direct manipulation: the conceptual framework for a hybrid human-computer interface

Abstract

This paper describes the development of a conceptual model of an interaction system for future human-computer interaction. It is suggested that an integrated system is the most promising solution for diverse users and tasks. A ‘ hybrid interaction system’ is considered, which tries to efficiently direct manipulation, menu selection, and natural language. The mechanism of the natural language interface module is described in more detail. Finally, the allocation of functionalities for generalized tasks on the conceptual model is considered from the taxonomic approach.     

Feminism and procedural content generation: toward a collaborative politics of computational creativity

ABSTRACT

Games now inhabit a space where creativity is no longer centered around human authorship. The use of procedural content generation has been embraced by industry, academics and fans as a means for reducing labor cost, providing additional replayable content for players, investigating computational creativity in a complex and multifaceted domain and enabling new kinds of playable experiences. This incorporation of computational creative labor confuses authorship, labor politics and responsibility for rhetoric embedded in the procedures by complicating the way in which the computer is portrayed to users, researchers and other developers. We can apply feminist methodologies attentive to questions of difference and power in systemic structures in order to better understand each of these questions in turn. This article presents an analysis of the post-anthropocentric phenomenon of computer creativity within games, via a feminist analysis of procedural content generating algorithms, its role in game design and its public portrayal.     

Human-agent service matching using natural language queries: system test and training

Smart environments, ambient intelligence and intelligent agents leave the user lost between large amounts of services. Ad-hoc networks, mobile agents and mobile devices make the set of available services dynamic over time and space, increasing the user’s problems to find the service he needs. Earlier, we presented a ServiceMatcher that can find the agent best fitting to the user’s natural language request. This paper presents performance results of the ServiceMatcher. The test queries come from human users in a realistic scenario (see our other paper in this issue). With a short training of the agent vocabularies, over 80% correct service matches are found.     

A full and efficient machine tractable dictionary for natural language processing: A revised version of the CUVOALD

A lexicon is an essential part of any natural language processing system. The size, content and format of the lexicon is crucial in determining the power and sophistication of a natural language processing system. However, a lexicon which provides comprehensive, consistent and accurate lexical information and which is in a format facilitating fast retrieval is not easily available. This paper reports on a project which aims at the development of such a lexicon. The resulting lexicon is actually the modified and extended version of the machine tractable version of the Oxford Advanced Learner's Dictionary. The modification and extension concentrate mainly on the aspects of comprehensiveness, consistency, explicitness, accuracy and the dictionary format. The modified and extended version is considered a desirable source of lexical information for any natural language processing system.Si-Qing Chen received her Ph.D. in computational linguistics (1992) from Guangzhou Institute of Foreign Languages. His research interests include natural language processing, computer-assisted language teaching, and computational lexicography. She is currently furthering her study and research at the University of Illinois at Urbana-Champaign. She has published several articles on psycholinguistics, language teaching, philosophy of language, and natural language processing in, amongst other journals, Language Learning and the CALICO Journal.Luomai Xu is an associate professor in the Department of English at Guangzhou Institute of Foreign Languages. He has been working on several projects and published several articles on natural language processing.     

Computer‐assisted foreign language instruction: task based vs. form focused

The purpose of this article is twofold: to describe a prototype for a computer‐assisted task‐based language instruction (CATBI) tool designed and developed for Turkish as a Foreign Language, and to report on the effectiveness of the CATBI tool. More specifically, this work discusses an experimental study that examined the role of teaching approach in foreign language development by comparing CATBI to computer‐assisted form‐focused language instruction (CAFFI) on language production in terms of accuracy, lexical complexity, and fluency. For a duration of 7 days, two intermediate‐level Turkish as a Foreign Language classes consisting of 28 high school students participated in this experiment. The classes were randomly assigned to two treatment groups: an experimental group with CATBI and a control group with CAFFI. Statistical analyses revealed that students in the CATBI group produced significantly better and more fluent language than students with CAFFI. However, no significant effects were found in terms of accuracy and lexical complexity of the language produced. Based on these results, it was concluded that CATBI is more effective than CAFFI in enhancing language production in general, and fluency in particular.