Language processing and acquisition in languages of Semitic, root-based, morphology / Joseph Shimron

This book addresses a fundamental question in the morphological analysis and representation of Semitic languages—namely, whether Semitic word morphology is root based or word based. As Shimron suggests, “there are reasons to view the templates, not the roots, as the more influential factor in determining Semitic morphology” (p. 5). Yet, as others would argue, there are reasons not to disregard the root-based hypothesis altogether. In the case of Arabic morphology, for example, verbal forms inherently contain three nonlinear levels: the consonantal root, the vowel pattern, and the templatic prosody. This nonlinear feature provided a perfect illustration of what has become termed in the literature as root-and-patterns morphology (McCarthy & Prince, 1986, 1990).

The effects of controlled language processing on listening comprehension and recall

This study seeks to determine the possible interactions between listening proficiency and the state of strategic self-awareness; second, and more importantly, to investigate the effects of learned strategies on listening comprehension and recall; and finally to describe the most common real-time listening comprehension problems faced by EFL learners and to compare the differences between learners with different listening abilities. After ten training sessions, an assessment was made to see whether or not well-learned strategies could provide students with ample opportunity to practice the comprehension and recall processes. The analyses of the data revealed the causes of ineffective low-level processing and provided insights to solve the problems of parsing. Moreover, the study reveals that explicit instruction of cognitive and metacognitive strategies is needed if a syllabus wishes to help learners improve their listening comprehension and become more-proficient at directing their own learning and development as L2 listeners.

Natural Language Checking with Program Checking Tools

Written text is an important component in the process of knowledge acquisition and communication. Poorly written text fails to deliver clear ideas to the reader no matter how revolutionary and ground-breaking these ideas are. Providing text with good writing style is essential to transfer ideas smoothly. While we have sophisticated tools to check for stylistic problems in program code, we do not apply the same techniques for written text. In this paper we present TextLint, a rule-based tool to check for common style errors in natural language. TextLint provides a structural model of written text and an extensible rule-based checking mechanism.

BIOMEDICAL LANGUAGE UNDERSTANDING AND EXTRACTION (BLUE-TEXT): A MINIMAL SYNTACTIC, SEMANTIC METHOD

Clinical text understanding (CTU) is of interest to health informatics because critical clinical information frequently represented as unconstrained text in electronic health records are extensively used by human experts to guide clinical practice, decision making, and to document delivery of care, but are largely unusable by information systems for queries and computations. Recent initiatives advocating for translational research call for generation of technologies that can integrate structured clinical data with unstructured data, provide a unified interface to all data, and contextualize clinical information for reuse in multidisciplinary and collaborative environment envisioned by CTSA program. This implies that technologies for the processing and interpretation of clinical text should be evaluated not only in terms of their validity and reliability in their intended environment, but also in light of their interoperability, and ability to support information integration and contextualization in a distributed and dynamic environment. This vision adds a new layer of information representation requirements that needs to be accounted for when conceptualizing implementation or acquisition of clinical text processing tools and technologies for multidisciplinary research. On the other hand, electronic health records frequently contain unconstrained clinical text with high variability in use of terms and documentation practices, and without commitmentto grammatical or syntactic structure of the language (e.g. Triage notes, physician and nurse notes, chief complaints, etc). This hinders performance of natural language processing technologies which typically rely heavily on the syntax of language and grammatical structure of the text. This document introduces our method to transform unconstrained clinical text found in electronic health information systems to a formal (computationally understandable) representation that is suitable for querying, integration, contextualization and reuse, and is resilient to the grammatical and syntactic irregularities of the clinical text. We present our design rationale, method, and results of evaluation in processing chief complaints and triage notes from 8 different emergency departments in Houston Texas. At the end, we will discuss significance of our contribution in enabling use of clinical text in a practical bio-surveillance setting.

Gramáticas lógicas: resolución de problemas en lenguaje natural

Esta tesis tiene por objeto estudiar las posibilidades de realizar en castellano tareas relativas a la resolución de problemas con sistemas basados en el conocimiento. En los dos primeros capítulos se plantea un análisis de la trayectoria seguida por las técnicas de tratamiento del lenguaje natural, prestando especial interés a los formalismos lógicos para la comprensión del lenguaje. Seguidamente, se plantea una valoración de la situación actual de los sistemas de tratamiento del lenguaje natural. Finalmente, se presenta lo que constituye el núcleo de este trabajo, un sistema llamado Sirena, que permite realizar tareas de adquisición, comprensión, recuperación y explicación de conocimiento en castellano con sistemas basados en el conocimiento. Este sistema contiene un subconjunto del castellano amplio pero simple formalizado con una gramática lógica. El significado del conocimiento se basa en la lógica y ha sido implementado en el lenguaje de programación lógica Prolog II vS. Palabras clave: Programación Lógica, Comprensión del Lenguaje Natural, Resolución de Problemas, Gramáticas Lógicas, Lingüistica Computacional, Inteligencia Artificial.---ABSTRACT---The purpose of this thesis is to study the possibi1 ities of performing in Spanish problem solving tasks with knowledge based systems. Ule study the development of the techniques for natural language processing with a particular interest in the logical formalisms that have been used to understand natural languages. Then, we present an evaluation of the current state of art in the field of natural language processing systems. Finally, we introduce the main contribution of our work, Sirena a system that allows the adquisition, understanding, retrieval and explanation of knowledge in Spanish with knowledge based systems. Sirena can deal with a large, although simple» subset of Spanish. This subset has been formalised by means of a logic grammar and the meaning of knowledge is based on logic. Sirena has been implemented in the programming language Prolog II v2. Keywords: Logic Programming, Understanding Natural Language, Problem Solving, Logic Grammars, Cumputational Linguistic, Artificial Intelligence.

Using Open Geographic Data to Generate Natural Language Descriptions for Hydrological Sensor Networks

Providing descriptions of isolated sensors and sensor networks in natural language, understandable by the general public, is useful to help users find relevant sensors and analyze sensor data. In this paper, we discuss the feasibility of using geographic knowledge from public databases available on the Web (such as OpenStreetMap, Geonames, or DBpedia) to automatically construct such descriptions. We present a general method that uses such information to generate sensor descriptions in natural language. The results of the evaluation of our method in a hydrologic national sensor network showed that this approach is feasible and capable of generating adequate sensor descriptions with a lower development effort compared to other approaches. In the paper we also analyze certain problems that we found in public databases (e.g., heterogeneity, non-standard use of labels, or rigid search methods) and their impact in the generation of sensor descriptions.

Autonomous Acquisition of Natural Language

An important part of human intelligence is the ability to use language. Humans learn how to use language in a society of language users, which is probably the most effective way to learn a language from the ground up. Principles that might allow an artificial agents to learn language this way are not known at present. Here we present a framework which begins to address this challenge. Our auto-catalytic, endogenous, reflective architecture (AERA) supports the creation of agents that can learn natural language by observation. We present results from two experiments where our S1 agent learns human communication by observing two humans interacting in a realtime mock television interview, using gesture and situated language. Results show that S1 can learn multimodal complex language and multimodal communicative acts, using a vocabulary of 100 words with numerous sentence formats, by observing unscripted interaction between the humans, with no grammar being provided to it a priori, and only high-level information about the format of the human interaction in the form of high-level goals of the interviewer and interviewee and a small ontology. The agent learns both the pragmatics, semantics, and syntax of complex sentences spoken by the human subjects on the topic of recycling of objects such as aluminum cans, glass bottles, plastic, and wood, as well as use of manual deictic reference and anaphora.

Human Immunodeficiency Virus Reverse Transcriptase and Protease Sequence Database: an expanded data model integrating natural language text and sequence analysis programs

The HIV Reverse Transcriptase and Protease Sequence Database is an on-line relational database that catalogs evolutionary and drug-related sequence variation in the human immunodeficiency virus (HIV) reverse transcriptase (RT) and protease enzymes, the molecular targets of anti-HIV therapy (http://hivdb.stanford.edu). The database contains a compilation of nearly all published HIV RT and protease sequences, including submissions from International Collaboration databases and sequences published in journal articles. Sequences are linked to data about the source of the sequence sample and the antiretroviral drug treatment history of the individual from whom the isolate was obtained. During the past year 3500 sequences have been added and the data model has been expanded to include drug susceptibility data on sequenced isolates. Database content has also been integrated with didactic text and the output of two sequence analysis programs.

Voice-processing technologies--their application in telecommunications.

As the telecommunications industry evolves over the next decade to provide the products and services that people will desire, several key technologies will become commonplace. Two of these, automatic speech recognition and text-to-speech synthesis, will provide users with more freedom on when, where, and how they access information. While these technologies are currently in their infancy, their capabilities are rapidly increasing and their deployment in today's telephone network is expanding. The economic impact of just one application, the automation of operator services, is well over $100 million per year. Yet there still are many technical challenges that must be resolved before these technologies can be deployed ubiquitously in products and services throughout the worldwide telephone network. These challenges include: (i) High level of accuracy. The technology must be perceived by the user as highly accurate, robust, and reliable. (ii) Easy to use. Speech is only one of several possible input/output modalities for conveying information between a human and a machine, much like a computer terminal or Touch-Tone pad on a telephone. It is not the final product. Therefore, speech technologies must be hidden from the user. That is, the burden of using the technology must be on the technology itself. (iii) Quick prototyping and development of new products and services. The technology must support the creation of new products and services based on speech in an efficient and timely fashion. In this paper I present a vision of the voice-processing industry with a focus on the areas with the broadest base of user penetration: speech recognition, text-to-speech synthesis, natural language processing, and speaker recognition technologies. The current and future applications of these technologies in the telecommunications industry will be examined in terms of their strengths, limitations, and the degree to which user needs have been or have yet to be met. Although noteworthy gains have been made in areas with potentially small user bases and in the more mature speech-coding technologies, these subjects are outside the scope of this paper.