7765314
Computer Understanding of Conventional Metaphoric Language
Metaphor is a conventional and ordinary part of language. An approach to metaphor, based on the explicit representation of knowledge about metaphors, has been developed. This approach asserts that the interpretation of conventional metaphoric language should proceed through the direct application of specific knowledge about the metaphors in the language. MIDAS (Metaphor Interpretation, Denotation, and Acquisition System) is a computer program that has been developed based upon this approach. MIDAS can be used to represent knowledge about conventional metaphors, interpret metaphoric language by applying this knowledge, and dynamically learn new metaphors as they are encountered during normal processing.
61042466
The berkeley UNIX consultant project
UC (UNIX Consultant) is an intelligent, natural language interface that allows naive users to learn about the UNIX2 operating system. UC was undertaken because the task was thought to be both a fertile domain for artificial intelligence (AI) research and a useful application of AI work in planning, reasoning, natural language processing, and knowledge representation.The current implementation of UC comprises the following components: a language analyzer, called ALANA, produces a representation of the content contained in an utterance; an inference component, called a concretion mechanism, that further refines this content; a goal analyzer, PAGAN, that hypothesizes the plans and goals under which the user is operating; an agent, called UCEgo, that decides on UC's goals and proposes plans for them; a domain planner, called KIP, that computes a plan to address the user's request; an expression mechanism, UCExpress, that determines the content to be communicated to the user, and a language production mechanism, UCGen, that expresses UC's response in English.UC also contains a component, called KNOME, that builds a model of the user's knowledge state with respect to UNIX. Another mechanism, UCTeacher, allows a user to add knowledge of both English vocabulary and facts about UNIX to UC's knowledge base. This is done by interacting with the user in natural language.All these aspects of UC make use of knowledge represented in a knowledge representation system called KODIAK. KODIAK is a relation-oriented system that is intended to have wide representational range and a clear semantics, while maintaining a cognitive appeal. All of UC's knowledge, ranging from its most general concepts to the content of a particular utterance, is represented in KODIAK.
2946678
Conventional Metaphor and the Lexicon
Metaphor and other forms of non-literal language are essential parts of language which have direct bearing on theories of lexical semantics. Neither narrow theories of lexical semantics, nor theories relying solely on world knowledge are sufficient to account for our ability to generate and interpret non-literal language. This paper presents an emerging approach that may provide such an account. This approach is based on systematic representations that capture non-literal language conventions, and mechanisms that can dynamically understand and learn new uses as they are encountered.
8592573
Contextual Spelling Correction Using Latent Semantic Analysis
Contextual spelling errors are defined as the use of an incorrect, though valid, word in a particular sentence or context. Traditional spelling checkers flag misspelled words, but they do not typically attempt to identify words that are used incorrectly in a sentence. We explore the use of Latent Semantic Analysis for correcting these incorrectly used words and the results are compared to earlier work based on a Bayesian classifier.
15685117
MetaBank: A Knowledge-Base of Metaphoric Language Conventions
The frequent and conventional use of nonliteral language has been a major stumbling block for natural language processing systems since the early machine translation efforts. Metaphor, metonymy, and indirect speech acts are among the most troublesome phenomena. Recent computational efforts addressing these problems have taken an approach that emphasizes the use of systematic knowledge about nonliteral language conventions. We are currently engaged in an effort to supply this knowledge in the case of conventional metaphor. We are constructing MetaBank: an empirically derived and theoretically motivated knowledge-base of English metaphorical conventions. This article describes our three-part approach to the construction of MetaBank: the collection of on-line textual resources and databases of linguistic generalizations, the development of a methodology for analyzing these resources, and the construction of a knowledge-base based on the preceding analyses.
33984452
Using System Networks to Build Rhetorical Structures
We are currently engaged in a project to study the generation of instructional texts for common consumer devices. Our initial efforts have focused on an exhaustive corpus-based analysis of instruction booklets for cordless telephones. In this paper, we present our analysis of the way the various processes used in this domain are expressed. Our emphasis here is on the relationship between the surface grammatical coding of these processes and the underlying rhetorical structure of the text. This analysis has been formalized using a systemic-functional framework, with the resulting system networks forming the basis for the Imagene text generation system.
44345524
Extracting Keyphrases from Spoken Audio Documents
Spoken audio documents are becoming more and more common on the World Wide Web, and this is likely to be accelerated by the widespread deployment of broadband technologies. Unfortunately, speech documents are inherently hard to browse because of their transient nature. One approach to this problem is to label segments of a spoken document with keyphrases that summarise them. In this paper, we investigate an approach for automatically extracting keyphrases from spoken audio documents. We use a keyphrase extraction system (Extractor) originally developed for text, and apply it to errorful Speech Recognition transcripts, which may contain multiple hypotheses for each of the utterances. We show that keyphrase extraction is an "easier" task than full text transcription and that keyphrases can be extracted with reasonable precision from transcripts with Word Error Rates (WER) as high as 62%. This robustness to noise can be attributed to the fact that keyphrase words have a lower WER than non-keyphrase words and that they tend to have more redundancy in the audio. From this we conclude that keyphrase extraction is feasible for a wide range of spoken documents, including less-than-broadcast casual speech. We also show that including multiple utterance hypotheses does not improve the precision of the extracted keyphrases.
8716869
Generating product-lines of product-families
GenVoca is a methodology and technology for generating product-lines, i.e. building variants of a program. The primitive components from which applications are constructed are refinements or layers, which are modules that implement a feature that many programs of a product-line can share. Unlike conventional components (e.g., COM, CORBA, EJB), a layer encapsulates fragments of multiple classes. Sets of fully formed classes can be produced by composing layers. Layers are modular, albeit unconventional, building blocks of programs. But what are the building blocks of layers? We argue that facets is an answer. A facet encapsulates fragments of multiple layers, and compositions of facets yields sets of fully formed layers. Facets arise when refinements scale from producing variants of individual programs to producing variants of multiple integrated programs, as typified byproduct families (e.g., MS Office). We present a mathematical model that explains relationships between layers and facets. We use the model to develop a generator for tools (i.e., product family) that are used in language-extensible Integrated Development Environments (IDEs).
28154888
Architecture of a Framework for Generic Assisting Conversational Agents
In this paper, we focus on the notion of Assisting Conversational Agents (ACA) that are embodied agents dedicated to the function of assistance for novice users of software components and/or web services. We discuss the main requirements of such agents and we emphasize the genericity issue arising in the dialogical part of such architectures. This prompts us to propose a mediator-based framework, using a dynamic symbolic representation of the runtime of the assisted components. Then we define three strategies for the development of the mediators that are validated by the implementation of experiences taken in various situations.
18962931
Analyzing xfig using the Rigi tool suite
An experiment is conducted on how well expert users of program comprehension tools are able to perform specific program understanding and maintenance tasks on the xfig drawing program using these tools. The paper reports on the experiences of the users of the Rigi reverse engineering tool suite. Rigi is an interactive, visual tool designed to help developers better understand and redocument their software. Rigi includes parsers to read the source code of the subject software and produce a graph of extracted artifacts such as procedures, variables, calls, and data accesses. To manage the complexity of the graph, an editor allows the software engineer to automatically or manually collapse related artifacts into subsystems. These subsystems typically represent concepts such as abstract data types or personnel assignments. The created hierarchy can be navigated, analyzed, and presented using various automatic or user-guided graphical layouts.
12923227
Levels of Representation in the Annotation of Emotion for the Specification of Expressivity in ECAs
In this paper we present a two-steps approach towards the creation of affective Embodied Conversational Agents (ECAs): annotation of a real-life nonacted emotional corpus and animation by copy-synthesis. The basis of our approach is to study how coders perceive and annotate at several levels the emotions observed in a corpus of emotionally rich TV video interviews. We use their annotations to specify the expressive behavior of an agent at several levels. We explain how such an approach can be useful for providing knowledge as input for the specification of non-basic patterns of emotional behaviors to be displayed by the ECA (e.g. which perceptual cues and levels of annotation are required for enabling the proper recognition of the emotions).