Computational Linguistics Commons^™

Automatic Creation Of Web Services From Extraction Ontologies, Deryle W. Lonsdale, Cui Tao, Yihong Ding

Faculty Publications

The Semantic Web promises to provide timely, targeted access to user-specified information online. Though standardized services exist for performing this work, specifying these services is too complex for most people. Annotating these services is also problematic. A similar situation exists for traditional information extraction, where ontologies are increasingly used to specify information used by various extraction methods. The approach we introduce in this paper involves converting such ontologies into executable Java code. These APIs act individually or compositionally as services for Semantic Web extraction.

Resolving Automatic Prepositional Phrase Attachments By Non-Statistical Means, Deryle W. Lonsdale, Michael B. Manookin

Faculty Publications

Prepositional-phrase attachment is a topic of active research in the field of computational linguistics. Properly attaching prepositional phrases to their pertinent constituent proves straightforward for humans, but inferring these attachments in a cognitive modeling system becomes difficult. For example, in the sentence, ‘Ralph threw the frisbee to John,’ the prepositional phrase ‘to John’ will attach to the verb phrase ‘threw’. In another example, ‘Joe saw the dog with fur,’ the prepositional phrase ‘with fur’ will attach directly to the noun phrase ‘the dog.’ Humans would have little difficulty resolving these examples, but for computers this would be difficult.

Combining Learning Approaches For Incremental On-Line Parsing, Deryle W. Lonsdale, Michael B. Manookin

Faculty Publications

This paper discusses the integration of two different machine learning approaches to modeling language, NL-Soar and analogical modeling (AM). The resulting hybrid system is capable of functionality that is not possible when using only one of the systems in isolation. After a brief introduction of each system, an explanation is given of how AM is used to provide information useful to NL-Soar for two tasks. Examples are given, and related issues are outlined.

Integrating Perception, Language And Problem Solving In A Cognitive Agent For A Mobile Robot., Deryle W. Lonsdale, D. Paul Benjamin, Damian M. Lyons

Faculty Publications

We are implementing a unified cognitive architecture for a mobile robot. Our goal is to endow a robot agent with the full range of cognitive abilities, including perception, use of natural language, learning and the ability to solve complex problems. The perspective of this work is that an architecture based on a unified theory of robot cognition has the best chance of attaining human-level performance.

This agent architecture is an integration of three theories: a theory of cognition embodied in the Soar system, the RS formal model of sensorimotor activity and an algebraic theory of decomposition and reformulation.

These three …

Nl-Soar Update, Deryle W. Lonsdale

Faculty Publications

No abstract provided.

Nl-Soar And Lg-Soar: Ongoing Work, Deryle W. Lonsdale

Faculty Publications

Goals:

Expand Soar knowledge and explore possible uses on-campus

Provide and support an NL capability to the Soar research community

Toolkits, resources, knowledge repositories

Carry out research into the cognitive modeling of linguistic performance

Minimum Mean Square Error Spectral Peak Envelope Estimation For Automatic Vowel Classification, Jaishree Venugopal

Electrical & Computer Engineering Theses & Dissertations

Spectral feature computations continue to be a very difficult problem for accurate machine recognition of speech. In this work, which focuses on vowels, a new spectral peak envelope method for vowel classification is developed, based on a missing frequency components model of speech recognition. According to the missing frequency components model, vowel recognition depends only on the spectral (harmonic) peaks. Smoothing and interpolation of the spectra, performed in the standard cepstral analysis method commonly used in automatic speech recognition, actually loses valuable information and results in reduced recognition accuracy. The new method for feature extraction presented in this thesis is …

Dialog Act Modeling For Automatic Tagging And Recognition Of Conversational Speech, Andreas Stolcke, Klaus Ries, Noah Coccaro, Elizabeth Shriberg, Rebecca Bates, Daniel Jurafsky, Paul Taylor, Rachel Martin, Carol Van Ess-Dykema, Marie Meteer

Integrated Engineering Department Publications

We describe a statistical approach for modeling dialogue acts in conversational speech, i.e., speech-act-like units such as Statement, Question, Back channel, Agreement, Disagreement, and Apology. Our model detects and predicts dialogue acts based on lexical, collocational, and prosodic cues, as well as on the discourse coherence of the dialogue act sequence. The dialogue model is based on treating the discourse structure of a conversation as a hidden Markov model and the individual dialogue acts as observations emanating from the model states. Constraints on the likely sequence of dialogue acts are modeled via a dialogue act n-gram. The statistical dialogue grammar …

The Variable Elision Of Unstressed Vowels In European Portuguese: A Case Study, David James Silva

David Silva

Visual Speech Training Aid For The Deaf, Subhashri Venkat

Electrical & Computer Engineering Theses & Dissertations

A computer-based vowel articulation training aid has been developed. A "continuous" acoustic-phonetic transformation is performed to map speech parameters to a lower dimensionality display space. There are two possible approaches to this transformation problem. The transformation could be either linear or a combination nonlinear/linear. The nonlinear transformation is performed using a multi-layered feedforward neural network with linear output layers. Speech parameters are extracted either from an analog filter bank arrangement (band energies) or by a digital signal processing procedure (Discrete Cosine Transform Coefficients). The speech parameters obtained from both methods correspond to the spectral envelope of the speech signals. The …

Concept Association, Sally Yeates Sedelow

Journal of the Arkansas Academy of Science

The complement to decomposition in scientific research is composition. In human language computing, composition is achieved by way of semantic association and the generation of strings of entities. That generation of strings takes place progressively: e.g., strings of symbols (words), strings of strings (sentences), strings of strings of strings (paragraphs), etc. The mathematical (topological, graph-theoretic) analysis of Roget's Thesaurus (1962) has opened a door onto a broad vista of potential achievements in such areas as artificial intelligence and expert systems, through the analysis of concept association, or concept composition.

A Comparison Of Norm-Referenced, Traditional, And Computer-Assisted Language Assessments, Michel P. Helmke

Masters Theses

Current literature in the field of communication disorders suggests that traditional norm-referenced tests may yield erroneous or misleading information regarding a child's level of language acquisition. Additional research suggests that the most valid and reliable technique for determining a client's level of linguistic expertise is language sampling and analysis. Language sampling and analysis has traditionally been rejected as a means of evaluation, especially for the school-age child, due to the length of time necessary to complete such analyses. In recent years, language sampling and analysis techniques have been redesigned as computer software application programs. Computer software application programs may significantly …