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.
39279518
Representing UNIX Domain Metaphors
The language used to describe technical domains like UNIX is filled with metaphor. An approach to metaphor, based on theexplicit representation of knowledge about metaphors, has beendeveloped. MIDAS (Metaphor Interpretation, Denotation, andAcquisition System) is a computer program that that has been developedbased upon this approach. MIDAS can be used to representknowledge about conventional metaphors, interpret metaphoric languageby applying this knowledge, and dynamically learn new metaphors asthey 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.
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.
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.
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.
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).
27507077
Temporal codes within a typology of cooperation between modalities
The Human-Machine Communication Department of LIMSI (LIMSI Report 1994), a laboratory of the French National Scientific Research Agency (CNRS), conducts research in the field of Pattern Recognition, Artificial Intelligence and Pattern Generation. Several approaches are currently investigated there for studying interactions between modalities: studies about the cognitive processes involved in human intermodal tasks (Denis and Cocude 1992; Gryl 1994; Daniel et al. 1994), image and language interactions for learning (Bordeaux 1993), human factors (Castaing and True 1993), symbolic approaches for designing multimodal human-computer interfaces (Bellik and Teil 1993; Bares et al. 1992), spatial reasoning (Ligozat 1992; Briffault 1992).
53305414
Fast Byzantine Consensus
We present the first protocol that reaches asynchronous Byzantine consensus in two communication steps in the common case. We prove that our protocol is optimal in terms of both number of communication steps and number of processes for two-step consensus. The protocol can be used to build a replicated state machine that requires only three communication steps per request in the common case. Further, we show a parameterized version of the protocol that is safe despite f Byzantine failures and, in the common case, guarantees two-step execution despite some number t of failures (t les f). We show that this parameterized two-step consensus protocol is also optimal in terms of both number of communication steps and number of processes
206630030
Statistical Gesture Recognition Through Modelling of Parameter Trajectories
The recognition of human gestures is a challenging problem that can contribute to a natural man-machine interface. In this paper, we present a new technique for gesture recognition. Gestures are modelled as temporal trajectories of parameters. Local sub-sequences of these trajectories are extracted and used to define an orthogonal space using principal component analysis. In this space the probabilistic density function of the training trajectories is represented by a multidimensional histogram, which builds the basis for the recognition. Experiments on three different recognition problems show the general utility of the approach.
26598527
Large Tandem Queueing Networks with Blocking
Systems consisting of many queues in series have been considered by Glynn and Whitt (1991) and Baccelli, Borovkov and Mairesse (2000). We extend their results to apply to situations where the queues have finite capacity and so various types of “blocking” can occur. The models correspond to max-plus type recursions, of simple form but in infinitely many dimensions; they are related to “percolation” problems of finding paths of maximum weight through a 2-dimensional lattice with random weights at the vertices. Topics treated include: laws of large numbers for the speed of customers progressing through the system; stationary behaviour for systems with external arrival processes; a functional central limit theorem describing the behaviour of the “front of the wave” progressing through a system which starts empty; stochastic orderings for waiting times of customers at successive queues. Several open problems are noted.