330 research outputs found
Prolegomena to a neurocomputational architecture for human grammatical encoding and decoding
The study develops a neurocomputational architecture for grammatical processing in language production and language comprehension (grammatical encoding and decoding, respectively). It seeks to answer two questions. First, how is online syntactic structure formation of the complexity required by natural-language grammars possible in a fixed, preexisting neural network without the need for online creation of new connections or associations? Second, is it realistic to assume that the seemingly disparate instantiations of syntactic structure formation in grammatical encoding and grammatical decoding can run on the same neural infrastructure? This issue is prompted by accumulating experimental evidence for the hypothesis that the mechanisms for grammatical decoding overlap with those for grammatical encoding to a considerable extent, thus inviting the hypothesis of a single “grammatical coder.” The paper answers both questions by providing the blueprint for a syntactic structure formation mechanism that is entirely based on prewired circuitry (except for referential processing, which relies on the rapid learning capacity of the hippocampal complex), and can subserve decoding as well as encoding tasks. The model builds on the “Unification Space” model of syntactic parsing developed by Vosse & Kempen (2000, 2008, 2009). The design includes a neurocomputational mechanism for the treatment of an important class of grammatical movement phenomena
An overview of computer-based natural language processing
Computer based Natural Language Processing (NLP) is the key to enabling humans and their computer based creations to interact with machines in natural language (like English, Japanese, German, etc., in contrast to formal computer languages). The doors that such an achievement can open have made this a major research area in Artificial Intelligence and Computational Linguistics. Commercial natural language interfaces to computers have recently entered the market and future looks bright for other applications as well. This report reviews the basic approaches to such systems, the techniques utilized, applications, the state of the art of the technology, issues and research requirements, the major participants and finally, future trends and expectations. It is anticipated that this report will prove useful to engineering and research managers, potential users, and others who will be affected by this field as it unfolds
VP\u3csup\u3e2\u3c/sup\u3e: The Role of User Modeling in Correcting Errors in Second Language Learning
This paper describes a system, VP2, that has been implemented to tutor non-native speakers in English. The system applies Artificial Intelligence techniques developed in Natural Language research. In particular, it differs from standard approaches by employing a model of its users to customize instruction based on knowledge of the student\u27s native language. The system focuses on the acquisition of English verb-particle and verb-prepositional phrase constructions. It diagnoses errors that students make due to interference of their native language. VP2 recognizes syntactic variation in English sentences, allowing freer translation. VP2 is a modular system: its model of a user\u27s native language can easily be replaced by a model of another language. Its correction strategy is based upon comparison of the native language model with a model of English. The problems and solutions presented in this paper are related to the more general question of how modeling previous knowledge facilitates instruction in a new skill
An analysis of the application of AI to the development of intelligent aids for flight crew tasks
This report presents the results of a study aimed at developing a basis for applying artificial intelligence to the flight deck environment of commercial transport aircraft. In particular, the study was comprised of four tasks: (1) analysis of flight crew tasks, (2) survey of the state-of-the-art of relevant artificial intelligence areas, (3) identification of human factors issues relevant to intelligent cockpit aids, and (4) identification of artificial intelligence areas requiring further research
MULTI-MODAL TASK INSTRUCTIONS TO ROBOTS BY NAIVE USERS
This thesis presents a theoretical framework for the design of user-programmable
robots. The objective of the work is to investigate multi-modal unconstrained natural
instructions given to robots in order to design a learning robot. A corpus-centred
approach is used to design an agent that can reason, learn and interact with a human in a
natural unconstrained way. The corpus-centred design approach is formalised and
developed in detail. It requires the developer to record a human during interaction and
analyse the recordings to find instruction primitives. These are then implemented into a
robot. The focus of this work has been on how to combine speech and gesture using
rules extracted from the analysis of a corpus. A multi-modal integration algorithm is
presented, that can use timing and semantics to group, match and unify gesture and
language. The algorithm always achieves correct pairings on a corpus and initiates
questions to the user in ambiguous cases or missing information. The domain of card
games has been investigated, because of its variety of games which are rich in rules and
contain sequences. A further focus of the work is on the translation of rule-based
instructions. Most multi-modal interfaces to date have only considered sequential
instructions. The combination of frame-based reasoning, a knowledge base organised as
an ontology and a problem solver engine is used to store these rules. The understanding
of rule instructions, which contain conditional and imaginary situations require an agent
with complex reasoning capabilities. A test system of the agent implementation is also
described. Tests to confirm the implementation by playing back the corpus are
presented. Furthermore, deployment test results with the implemented agent and human
subjects are presented and discussed. The tests showed that the rate of errors that are
due to the sentences not being defined in the grammar does not decrease by an
acceptable rate when new grammar is introduced. This was particularly the case for
complex verbal rule instructions which have a large variety of being expressed
Studies in the linguistic sciences. 08 (1978)
MLA international bibliography of books and articles on the modern languages and literatures (Complete edition) 0024-821
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Planning multisentential English text using communicative acts
The goal of this research is to develop explanation presentation mechanisms for knowledge based
systems which enable them to define domain terminology and concepts, narrate events, elucidate plans,
processes, or propositions and argue to support a claim or advocate action. This requires the development
of devices which select, structure, order and then linguistically realize explanation content as coherent and
cohesive English text.
With the goal of identifying generic explanation presentation strategies, a wide range of naturally
occurring texts were analyzed with respect to their communicative sttucture, function, content and intended
effects on the reader. This motivated an integrated theory of communicative acts which characterizes text at
the level of rhetorical acts (e.g., describe, define, narrate), illocutionary acts (e.g., inform, request), and
locutionary acts (e.g., ask, command). Taken as a whole, the identified communicative acts characterize
the structure, content and intended effects of four types of text: description, narration, exposition,
argument. These text types have distinct effects such as getting the reader to know about entities, to know
about events, to understand plans, processes, or propositions, or to believe propositions or want to
perform actions. In addition to identifying the communicative function and effect of text at multiple levels
of abstraction, this dissertation details a tripartite theory of focus of attention (discourse focus, temporal
focus, and spatial focus) which constrains the planning and linguistic realization of text.
To test the integrated theory of communicative acts and tripartite theory of focus of attention, a text
generation system TEXPLAN (Textual EXplanation PLANner) was implemented that plans and
linguistically realizes multisentential and multiparagraph explanations from knowledge based systems. The
communicative acts identified during text analysis were formalized as over sixty compositional and (in
some cases) recursive plan operators in the library of a hierarchical planner. Discourse, temporal, and
spatial focus models were implemented to track and use attentional information to guide the organization
and realization of text. Because the plan operators distinguish between the communicative function (e.g.,
argue for a proposition) and the expected effect (e.g., the reader believes the proposition) of communicative
acts, the system is able to construct a discourse model of the structure and function of its textual responses
as well as a user model of the expected effects of its responses on the reader's knowledge, beliefs, and
desires. The system uses both the discourse model and user model to guide subsequent utterances. To test
its generality, the system was interfaced to a variety of domain applications including a neuropsychological
diagnosis system, a mission planning system, and a knowledge based mission simulator. The system
produces descriptions, narrations, expositions, and arguments from these applications, thus exhibiting a
broader range of rhetorical coverage than previous text generation systems
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