Language Interpretation and Meaning

For the past twenty to thirty years, a good part of the domain of linguistics has been occupied by what has been called discourse analysis. Whereas syntax and semantics are concerned by the sentence and the units from which the sentence is built, discourse analysis claims that interpretation cannot accounted for at the level of the sentence and that a bigger unit, such as discourse should be used to account for language interpretation. We want to show here that discourse is not, in any sense, a well defined object and that, though it is certainly necessary to analyze how a given sequence of sentences is processed and understood, the notion of discourse, A and related notions such as coherence does not have much to say about it. We rely on epistemological considerations about the necessity of a moderate reductionism and sketch on account of linguistic interpretation which accounts for contextual factors in linguistic interpretation through the notion of utterance (vs. sentence) and a development of Sperber & Wilsons Relevance Theory.

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Enriched Meanings

10.1093/oso/9780198847854.001.0001 ◽

2020 ◽

Author(s):

Ash Asudeh ◽

Gianluca Giorgolo

Keyword(s):

Cognitive Science ◽

Programming Languages ◽

Category Theory ◽

Worst Case ◽

Disciplinary Boundaries ◽

Semantics Of Programming Languages ◽

Basic Meaning ◽

Language Interpretation ◽

Major Branch ◽

Compositional Properties

This book presents a theory of enriched meanings for natural language interpretation. Certain expressions that exhibit complex effects at the semantics/pragmatics boundary live in an enriched meaning space while others live in a more basic meaning space. These basic meanings are mapped to enriched meanings just when required compositionally, which avoids generalizing meanings to the worst case. The theory is captured formally using monads, a concept from category theory. Monads are also prominent in functional programming and have been successfully used in the semantics of programming languages to characterize certain classes of computation. They are used here to model certain challenging linguistic computations at the semantics/pragmatics boundary. Part I presents some background on the semantics/pragmatics boundary, informally presents the theory of enriched meanings, reviews the linguistic phenomena of interest, and provides the necessary background on category theory and monads. Part II provides novel compositional analyses of the following phenomena: conventional implicature, substitution puzzles, and conjunction fallacies. Part III explores the prospects of combining monads, with particular reference to these three cases. The authors show that the compositional properties of monads model linguistic intuitions about these cases particularly well. The book is an interdisciplinary contribution to Cognitive Science: These phenomena cross not just the boundary between semantics and pragmatics, but also disciplinary boundaries between Linguistics, Philosophy and Psychology, three of the major branches of Cognitive Science, and are here analyzed with techniques that are prominent in Computer Science, a fourth major branch. A number of exercises are provided to aid understanding, as well as a set of computational tools (available at the book's website), which also allow readers to develop their own analyses of enriched meanings.

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Design and Development of a Humanoid Robot for Sign Language Interpretation

SN Computer Science ◽

10.1007/s42979-021-00627-3 ◽

2021 ◽

Vol 2 (3) ◽

Author(s):

Ragib Amin Nihal ◽

Nawara Mahmood Broti ◽

Shamim Ahmed Deowan ◽

Sejuti Rahman

Keyword(s):

Sign Language ◽

Humanoid Robot ◽

Design And Development ◽

Language Interpretation

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ECG Prediction Based on Classification via Neural Networks and Linguistic Fuzzy Logic Forecaster

The Scientific World JOURNAL ◽

10.1155/2015/205749 ◽

2015 ◽

Vol 2015 ◽

pp. 1-10 ◽

Cited By ~ 2

Author(s):

Eva Volna ◽

Martin Kotyrba ◽

Hashim Habiballa

Keyword(s):

Neural Networks ◽

Time Series ◽

Ecg Signals ◽

Detection Systems ◽

Language Interpretation ◽

Different Types ◽

Time Courses ◽

Natural Language Interpretation ◽

Unique Capability

The paper deals with ECG prediction based on neural networks classification of different types of time courses of ECG signals. The main objective is to recognise normal cycles and arrhythmias and perform further diagnosis. We proposed two detection systems that have been created with usage of neural networks. The experimental part makes it possible to load ECG signals, preprocess them, and classify them into given classes. Outputs from the classifiers carry a predictive character. All experimental results from both of the proposed classifiers are mutually compared in the conclusion. We also experimented with the new method of time series transparent prediction based on fuzzy transform with linguistic IF-THEN rules. Preliminary results show interesting results based on the unique capability of this approach bringing natural language interpretation of particular prediction, that is, the properties of time series.

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