Mitre Corporation

About: Mitre Corporation is a company organization based out in Bedford, Massachusetts, United States. It is known for research contribution in the topics: Air traffic control & National Airspace System. The organization has 4884 authors who have published 6053 publications receiving 124808 citations. The organization is also known as: Mitre & MITRE.

Intelligent user interfaces: an introduction

Abstract: Intelligent user interfaces promise to improve the interaction for all. Drawing upon material from the recently completed Readings in Intelligent User Interfaces (IUI) (Maybury and Wahlster, 1998), this tutorial will define terms, outline the history, describe key subfields, and exemplify and demonstrate intelligent user interfaces in action.

Continuous automatic speech recognition by lipreading

Abstract: This study describes the design and implementation of a novel continuous speech recognizer that uses optical information from the oral-cavity shadow of a speaker. The system uses hidden Markov models (HMMs) trained to discriminate optical information and achieves a recognition rate of 25.3 percent on 150 test sentences. This is the first system to accomplish continuous optical automatic speech recognition (OASR). This level of performance--without the use of syntactical, semantic, or any other contextual guide to the recognition process--indicates that OASR may be used as a major supplement for robust multi-modal recognition in noisy environments. Additionally, new features important for OASR were discovered, and novel approaches to vector quantization, training, and clustering were utilized. This study contains three major components. First, it hypothesize 35 static and dynamic optical features to characterize the shadow of the oral-cavity for the speaker. Using the corresponding correlation matrix and a principal component analysis, the study discarded 22 oral-cavity features. The remaining 13 oral-cavity features are mostly dynamic features, unlike the static features used by previous researchers. Second, the study merged phonemes that appear optically similar on the speaker's oral-cavity region into visemes. The visemes were objectively analyzed and discriminated using HMM and clustering algorithms. Most significantly, the visemes for the speaker, obtained through computation, are consistent with the phoneme-to-viseme mapping discussed by most lipreading experts. This similarity, in a sense, verifies the selection of oral-cavity features. Third, the study trained the HMMs to recognize, without a grammar, a set of sentences having a perplexity of 150, using visemes, trisemes (triplets of visemes), and generalized trisemes (clustered trisemes). The system achieved recognition rates of 2 percent, 12.7 percent, and 25.3 percent using, respectively, viseme HMMs, triseme HMMs, and generalized triseme HMMs. The study concludes that methodologies used in this investigation demonstrate the need for further research on continuous OASR and on the integration of optical information with other recognition methods. While this study focuses on the feasibility, validity, and segregated contribution of exclusively continuous OASR, future highly robust recognition systems should combine optical and acoustic information with syntactic, semantic and pragmatic aids.

An examination of the effects of requirements changes on software maintenance releases

Abstract: Requirements are the foundation of the software release process. They provide the basis for estimating costs and schedules, as well as developing design and testing specifications. When requirements have been agreed on by both clients and maintenance management, then adding to, deleting from, or modifying those existing requirements during the execution of the software maintenance process impacts the maintenance cost, schedule, and quality of the resulting product. The basic problem is not the changing in itself, but rather the inadequate approaches for dealing with changes in a way that minimizes and communicates the impact to all stakeholders. Using data collected from one organization on 44 software releases spanning seven products, this paper presents two quantitative techniques for dealing with requirements change in a maintenance environment. First, exploratory data analysis helps one to understand the sources, frequency, and types of changes being made. Second, a regression model helps managers communicate the cost and schedule effects of changing requirements to clients and other release stakeholders. These two techniques can help an organization provide a focus for management action during the software maintenance process. Copyright © 1999 John Wiley & Sons, Ltd.

Soundness of formal encryption in the presence of key-cycles

Abstract: Both the formal and the computational models of cryptography contain the notion of message equivalence or indistinguishability. An encryption scheme provides soundness for indistinguishability if, when mapping formal messages into the computational model, equivalent formal messages are mapped to indistinguishable computational distributions. Previous soundness results are limited in that they do not apply when key-cycles are present. We demonstrate that an encryption scheme provides soundness in the presence of key-cycles if it satisfies the recently-introduced notion of key-dependent message (KDM) security. We also show that soundness in the presence of key-cycles (and KDM security) neither implies nor is implied by security against chosen ciphertext attack (CCA-2). Therefore, soundness for key-cycles is possible using a new notion of computational security, not possible using previous such notions, and the relationship between the formal and computational models extends beyond chosen-ciphertext security.

SpatialML: Annotation Scheme, Corpora, and Tools

Abstract: SpatialML is an annotation scheme for marking up references to places in natural language. It covers both named and nominal references to places, grounding them where possible with geo-coordinates, including both relative and absolute locations, and characterizes relationships among places in terms of a region calculus. A freely available annotation editor has been developed for SpatialML, along with a corpus of annotated documents released by the Linguistic Data Consortium. Inter-annotator agreement on SpatialML is 77.0 F-measure for extents on that corpus. An automatic tagger for SpatialML extents scores 78.5 F-measure. A disambiguator scores 93.0 F-measure and 93.4 Predictive Accuracy. In adapting the extent tagger to new domains, merging the training data from the above corpus with annotated data in the new domain provides the best performance.