Digital Commons Network^™

Speaker Recognition By Hidden Markov Models And Neural Networks, Erik J. Zeek

Theses and Dissertations

As humans, we develop the ability to identify people by their voice at an early age. Getting computers to perform the same task has proven to be an interesting problem. Speaker recognition involves two applications, speaker identification and speaker verification. Both applications are examined in this effort. Two methods are employed to perform speaker recognition. The first is an enhancement of hidden Markov models. Rather than alter some part of the model itself, a single-layer perceptron is added to perform neural post-processing. The second solution is the novel application of an enhanced Feature Space Trajectory Neural Network to speaker recognition. …

A Domain Independent Framework For Developing Knowledge Based Computer Generated Forces, James L. Benslay Jr.

Theses and Dissertations

Computer Generated Forces (CGFs) are important players in Distributed Interactive Simulation (DIS) exercises. A problem with CGFs is that they do not exhibit sufficient human behaviors to make their use effective. The SOAR approach has yielded a human cognitive model that can be applied to CGFs, but this is extremely complex. The product of the research reported in this thesis is a much less complex behavioral framework for a CGF that is easy to validate, revise, and maintain. To support this, an existing, domain independent CGF architecture is discussed and applied to an experimental CGF. Techniques for modeling the knowledge …

Puzzles, Patterns Drums: The Dawn Of Mathematics In Rwanda And Burundi., D. Huylebrouck

Humanistic Mathematics Network Journal

No abstract provided.

A Fertility Channel Model For Post-Correction Of Continuous Speech Recognition, Eric K. Ringger, James F. Allen

Faculty Publications

We have implemented a post-processor called SPEECHPP to correct word-level errors committed by an arbitrary speech recognizer. Applying a noisy-channel model, SPEECHPP uses a Viterbi beam-search that employs language and channel models. Previous work demonstrated that a simple word-for-word channel model was sufficient to yield substantial incieases in word accuracy. This paper demonstrates that some improvements in word accuracy result from augmenting the channel model with an account of word fertility in the channel. This work further demonstrates that a modern continuous speech recognizer can be used in "black-box" fashion for robustly recognizing speech for which the recognizer was not …

The Role Of Written And Verbal Expression In Improving Communication Skills For Students In An Undergraduate Chemistry Program, Brian P. Coppola, Douglas S. Daniels

Chemistry Faculty Publications

Proofreading, editing, and critique, the customary assessment tools scientists use to evaluate professional journal articles, grant applications, and any other writing, can be applied equally well in introductory science instruction. Such feedback is, in fact, crucial to growth and development. When learning anything new, students and faculty alike rely heavily on sources other than themselves (‘external editors’) to assess their understanding as they develop self-assessment skills (or ‘internal editors’). Although they rarely describe it in these terms, faculty nonetheless assume that students have developed and refined their internal skills by the time they take examinations and write term papers. Unfortunately, …

A Last Word On Pattern Frequency Occurences In A Markovian Sequence?, Mireille Régnier, Wojciech Szpankowski

Department of Computer Science Technical Reports

No abstract provided.

Visual Speech Recognition Using Multiple Deformable Lip Models, Devi Chandramohan

Electrical & Computer Engineering Theses & Dissertations

Motivated by the fact that human speech perception is a bimodal process (auditory and visual), several researchers have designed and implemented automatic speech recognition (ASR) systems consisting of both audio and visual subsystems, and shown improved performance relative to traditional purely auditory systems. Several visual speech reading approaches have used deformable templates to model the shape of a speaker's lips. Deformable templates are models of image objects, which can be deformed by adjusting a set of parameters to match the object in some optimal way, as defined by a cost function. Using a single deformable lip model has disadvantages such …

Observer: An Approach For Query Processing In Global Information Systems Based On Interoperation Across Pre-Existing Ontologies, Eduardo Mena, Vipul Kashyap, Amit P. Sheth, Arantza Illarramendi

Kno.e.sis Publications

The huge number of autonomous and heterogeneous data repositories accessible on the “global information infrastructure” makes it impossible for users to be aware of the locations structure/organization, query languages and semantics of the data in various repositories. There is a critical need to complement current browsing, navigational and information retrieval techniques with a strategy that focuses on information content and semantics. In any strategy that focuses on information content, the most critical problem is that of different vocabularies used to describe similar information across domains. We discuss a scalable approach for vocabulary sharing. The objects in the repositories are represented …

A Robust System For Natural Spoken Dialogue, Eric K. Ringger, James F. Allen, Bradford W. Miller, Teresa Sikorski

Faculty Publications

This paper describes a system that leads us to believe in the feasibility of constructing natural spoken dialogue systems in task-oriented domains. It specifically addresses the issue of robust interpretation of speech in the presence of recognition errors. Robustness is achieved by a combination of statistical error post-correction, syntactically- and semantically-driven robust parsing, and extensive use of the dialogue context. We present an evaluation of the system using time-to-completion and the quality of the final solution that suggests that most native speakers of English can use the system successfully with virtually no training.

Error Correction Via A Post-Processor For Continuous Speech Recognition, Eric K. Ringger, James F. Allen

Faculty Publications

This paper presents a new technique for overcoming several types of speech recognition errors by post-processing the output of a continuous speech recognizer. The post-processor output contains fewer errors, thereby making interpretation by higher-level modules, such as a parser, in a speech understanding system more reliable. The primary advantage to the post-processing approach over existing approaches for overcoming SR errors lies in its abilityto introduce options that are not available in the SR module’s output. This work provides evidence for the claim that a modern continuous speech recognizer can be used successfully in “black-box” fashion for robustly interpreting spontaneous utterances …

The Annual Meeting Of The Iowa Academy Of Science April 26-27, 1996 [Program, 108th Meeting], Iowa Academy Of Science

Iowa Academy of Science Documents

Contents:

Program Summary --- 4
General Session Speakers --- 7
Awards --- 10
Symposia Programs --- 11
Poster Session --- 13
Map --- Centerfold
Section Programs/Special Sessions --- 15
Agricultural Sciences --- 15
Anthropology --- 16
Botany --- 18
Biology: Cellular, Molecular, & Micro --- 19
Chemistry: Inorganic --- 20
Chemistry: Organic --- 21
Conservation --- 22
Engineering --- 23
Geology --- 24
Linguistics/Psychology --- 25
Physics --- 26
Physiology --- 27
Zoology --- 29
Science Teaching --- 30
Local Arrangements Committee --- 31
Annual Meeting Committee --- 31
IAS Officers & Directors --- 32
Future Meetings --- 32

Adaptive Integration Of Audio And Visual Information Using Discrete And Semi-Continuous Hidden Markov Models In Audiovisual Automatic Speech Recognition, Qin Su

Electrical & Computer Engineering Theses & Dissertations

An audiovisual semi-continuous hidden Markov model (HMM)-based Automatic Speech Recognition (ASR) system and an improved method of integrating audio and visual information in an audiovisual discrete HMM-based ASR system are investigated.

In the audiovisual discrete HMM, an adaptive integration formulation is employed, which incorporates the integration into the HMM at a pre-categorical stage. A visual weighting parameter is determined automatically, which allows the relative contribution of audio and visual information to be adjusted adaptively. Using an adaptive weight, the accuracy increased by 13% compared to the same model with no adaptive weight.

The semi-continuous HMM is a class of models …

Speech Feature Computation For Visual Speech Articulation Training, Stefan Auberg

Electrical & Computer Engineering Theses & Dissertations

A new version of the Visual Speech Articulation Training Aid was implemented which provides real-time visual feedback for speech articulation training. This version was migrated to a Windows Multimedia PC from a previous version which used a Personal Computer (PC) system and additional specialized and expensive custom hardware. This new version will make the system more available to schools and private users. A new method was developed for computing spectral/temporal features which characterize the speech sounds. In addition to the typical frame-based spectral analysis parameters, the new method represents temporal changes of the spectrum with a small number of features. …

Generalized Hidden Filter Markov Models Applied To Speaker Recognition, John M. Colombi

Theses and Dissertations

Classification of time series has wide Air Force, DoD and commercial interest, from automatic target recognition systems on munitions to recognition of speakers in diverse environments. The ability to effectively model the temporal information contained in a sequence is of paramount importance. Toward this goal, this research develops theoretical extensions to a class of stochastic models and demonstrates their effectiveness on the problem of text-independent (language constrained) speaker recognition. Specifically within the hidden Markov model architecture, additional constraints are implemented which better incorporate observation correlations and context, where standard approaches fail. Two methods of modeling correlations are developed, and their …

Unsupervised Algorithms For Learning Emergent Spatio-Temporal Correlations, Chaitanya Tumuluri

Electrical Engineering and Computer Science - Technical Reports

Many applications require the extraction of spatiotemporal correlations among dynamically emergent features of non-stationary distributions. In such applications it is not possible to obtain an a priori analytical characterization of the emergent distribution. This paper extends the Growing Cell Structures (GCS) network and presents two novel (GIST and GEST) networks, which combine unsupervised feature-extraction and Hebbian learning, for tracking such emergent correlations. The networks were successfully tested on the challenging Data Mapping problem, using an execution driven simulation of their implementation in hardware. The results of the simulations show the successful use of the GIST and GEST networks for extracting …

Increasing Esl Student Language Production And Altering The Affective Climate In A Mountain Community High School, Linda Louise Hanneman

Theses Digitization Project

No abstract provided.

A Constructivist Study Of University Curricular Attributes And Faculty Leadership In Support Of Environmental Sustainability, Esther Jane Ross, Gary Mcmane

Theses Digitization Project

No abstract provided.

Collections Summary For Dugway Proving Ground, Utah, U.S. Army Corps Of Engineers

Elusive Documents

No abstract provided.

Semantic And Schematic Similarities Between Database Objects: A Context-Based Approach, Vipul Kashyap, Amit P. Sheth

Kno.e.sis Publications

In a multidatabase system, schematic conflicts between two objects are usually of interest only when the objects have some semantic similarity. We use the concept of semantic proximity, which is essentially an abstraction/mapping between the domains of the two objects associated with the context of comparison. An explicit though partial context representation is proposed and the specificity relationship between contexts is defined. The contexts are organized as a meet semi-lattice and associated operations like the greatest lower bound are defined. The context of comparison and the type of abstractions used to relate the two objects form the basis of a …

Iowa Academy Of Science Membership Directory, 1996-97, Iowa Academy Of Science

Iowa Academy of Science Documents

Contents:

Editorial Board, Journal ... 5
Committees ... 6
Sections ... 18
ISTS Regional Directors ... 22
Awards of Merit ... 24
Excellence in Science Teaching Awards ... 25
Past Presidents ... 26
Membership Roster ... 27

Election Day Puzzle, 1996, Jeremiah Farrell

Scholarship and Professional Work - LAS

Jeremiah Farrell's famous 1996 Election Day Puzzle. The puzzle was released the day before the results of the election were announced and the answer to 39 across could have been either CLINTON or BOBDOLE.

Iowa Academy Of Science 108th Annual Meeting [1996]: Advance Program, Iowa Academy Of Science

Iowa Academy of Science Documents

Contains information about the schedule and presentations for the 1996 annual meeting of the Iowa Academy of Science.

Negotiation As A Resource Allocation Process, Fernando Tohme

All Computer Science and Engineering Research

The main economic-theoretic approcahes to the problem of resource allocation make little if any reference to negotiation processes. These processes are fundamentally linguistic, based on the exchange of messages among agents. Communication being so fundamental in the characterization of negotiation processes, the analysis of negotiation must emphasize on the structure of the language in which the negotiations take place. Computer science and particularly Artificial Intelligence have provided interesting insights about that linguistic structure. In the first part of this work we present a brief survey of the literature on resource allocation processes in which communication among agents plays a relevant …

An Investigation Into An Effective Method Of Automatically Analysing Oracle Applications To Count Function Points, J. L. Wong

Theses : Honours

Function Point Analysis (FPA) is a synthetic software estimation metric used for computing the size and complexity of applications. It was first introduced by Allan. J. Albrecht during the mid-seventies, as a result of a lengthy research based on applications that were developed using COBOL and PL/1 programming languages. The purpose of this research· is to investigate the possibility, and the most effective method, of automatically performing a Function Point Analysis on Oracle applications that consist of Oracle Forms and Oracle Reports. The research revealed a seemingly lack of other researches on this topic. As FPA was invented a few …

A Systematic Tradeoff Methodology For Acquiring And Validating Imprecise Requirements, J. Yen, Xiaoqing Frank Liu, W. A. Tiao

Computer Science Faculty Research & Creative Works

Requirement analysis is one of the most important phases in a software development process. Existing requirement methodologies are limited in specifying requirements that are usually vague and imprecise, and in supporting tradeoff analysis between the conflicting requirements. In this paper, the elasticity of imprecise requirements is captured using fuzzy logic to facilitate tradeoffs between conflicting requirements. Based on the marginal rate of substitution in decision science, we have developed a systematic approach to elicit the structures and the parameters of imprecise requirements, to validate the scheme for aggregating requirements, and to assess relative priorities of conflicting requirements.

Glacial Deposits, Vol. 24, 1995-1996, Department Of Geography-Geology

Glacial Deposits

Newsletter of the Department of Geography-Geology

An Adaptive Fuzzy Logic Controller For Intelligent Networking And Control, Irshad Nainar

Theses: Doctorates and Masters

In this thesis, we present a fuzzy logic control scheme to regulate the flow of traffic approaching a set of intersections. An adaptive Fuzzy Logic Traffic Controller (FLTC) is used to adjust the green phase split of the north-south and east-west approaches of a set of traffic signals based on the actual traffic approaching the intersection. Each intersection is coordinated with its neighbouring intersections by adjusting the offset of the local intersection. The offset is adjusted by a local fuzzy logic controller loacted at each intersection. A new fuzzy control scheme, using a supervisory Fuzzy Logic Controller, is also proposed …

On The Impact Of Forgetting On Learning Machines, Rūsiņš Freivalds, Efim Kinber, Carl H. Smith

School of Computer Science & Engineering Faculty Publications

People tend not to have perfect memories when it comes to learning, or to anything else for that matter. Most formal studies of learning, however, assume a perfect memory. Some approaches have restricted the number of items that could be retained. We introduce a complexity theoretic accounting of memory utilization by learning machines. In our new model, memory is measured in bits as a function of the size of the input. There is a hierarchy of learnability based on increasing memory allotment. The lower bound results are proved using an unusual combination of pumping and mutual recursion theorem arguments. For …

Automatic Office Document Classification And Information Extraction, Xiaolong Hao

Dissertations

TEXPR.OS (TEXt PROcessing System) is a document processing system (DPS) to support and assist office workers in their daily work in dealing with information and document management. In this thesis, document classification and information extraction, which are two of the major functional capabilities in TEXPROS, are investigated.

Based on the nature of its content, a document is divided into structured and unstructured (i.e., of free text) parts. The conceptual and content structures are introduced to capture the semantics of the structured and unstructured part of the document respectively. The document is classified and information is extracted based on the analyses …

Neuro-Fuzzy Models For Classification And Rule Generation., Sushmita Mitra Dr.

Doctoral Theses

Machine recognition [1, 2] of patterns can be viewed as a two-fold task, consisting of learning the invariant and common properties of a set of samples characterizing a class, and of deciding a new sample as a possible member of the class by noting that it has properties common to those of the set of samples. In other words, pattern recognition by computers can be described as a transformation from the measurenment space M to the feature space F and finally to the decision space D (1), i.e., M ⟶F⟶D.Here, the mapping 6 : F⟶D is the decision function and …