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IIT Hyderabad

Fundamental tensions exist between formal-logical approaches and cognitive approaches to linguistic meaning. The divergence arises from the fundamental differences in nature and form between formal/mathematical structures of natural language meaning and their cognitive representations. While the former are abstract and logical categories of representations, the latter are ultimately embodied and grounded in sensory-motor systems of the brain. This article aims to motivate a unifying theory/formalism of linguistic meaning from a general biologically integrative perspective in the context of current theorizing in linguistics, neurobiology and cognitive sciences on human language meaning within which two divergent approaches for the mathematical and cognitive aspects of linguistic meaning exist. The tensions can be somewhat neutralized if formal-mathematical structures and cognitive representations of natural language meaning can be shown to have representational duality and unity in brain dynamics. This work shows a broad outline of one, if not the only one, path toward this vision. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Department of Liberal Arts

Communicative and Integrative Biology

Towards a unifying theory of linguistic meaning

Natural language meaning has properties of both cognitive representations and formal/mathematical structures. But it is not clear how they actually relate to one another. The central aim of this article is to show that properties of cognitive representations and formal/mathematical structures of natural language meaning, albeit apparently divergent, can be united, as far as the basic properties of semantic structures are concerned. Thus, this article will formulate the form of unified representations for semantic structures. With this goal, this article takes into account standard formal-semantic representations and also Discourse Representation Theory (DRT) representations on the one hand and semantic representations in different versions of Conceptual/Cognitive Semantics (Jackendoff's, Langacker's and Talmy's approaches to Conceptual/Cognitive Semantics) and representations of Mental Spaces (Fauconnier's approach) on the other hand. The rationale behind the selection of these approaches is that the representations of semantic structures under these approaches are all amenable to unification. It must be emphasized that showing that the representations of semantic structures under these approaches can be unified does not simply amount to unifying these theories/approaches in toto. Rather, it is to demonstrate that cognitive representations and formal/mathematical structures can be shown to be inter-translatable for at least some accounts of linguistic meaning. © 2023 the author(s), published by De Gruyter.

Fulltext

Open Linguistics

Towards a unified representation of linguistic meaning

This article will provide a unifying perspective on perception and cognition via the route of linguistic representations of emotion. Linguistic representations of emotions provide a fertile ground for explorations into the nature and form of integration of perception and cognition because emotion has facets of both perceptual and cognitive processes. In particular, this article shows that certain types of linguistic representations of emotion allow for the integration of perception and cognition through a series of steps and operations in cognitive systems, whereas certain other linguistic representations of emotion are not so representationally structured as to permit the unity of perception and cognition. It turns out that the types of linguistic representations of emotion that readily permit the desired unity of perception and cognition are exactly those that are linguistically encoded emotive representations of everyday objects, events, and things around us. It is these ordinary objects, events and things that provide the scaffolding for task-dependent or goal-oriented activities of cognitive systems including autonomous systems. In this way, cognitive systems can be saliently tuned to the outer world by being motivated and also subtly governed by emotion-driven representations. This helps not only tie together perceptual and cognitive processes via the interface between language and emotive representations, but also reveal the limits of emotive representations in amalgamating perceptual and cognitive processes in cognitive systems. Copyright © 2022 Mondal.

Frontiers in Psychology

A Unifying Perspective on Perception and Cognition Through Linguistic Representations of Emotion

This paper argues that a simple system of meaning relations drawn from words/lexical items in a natural language and framed in terms of syntax-free relations in linguistic texts can help ground linguistic predicates or concepts thereof in a number of meaning relations. These relations are constrained by the logical structures of linguistic meanings across sentence and discourse contexts. Significantly, such meaning relations are not defined over, or do not ride on, the syntactic structure of a given language. Nor do they (necessarily) turn on compositional relations for the computation of meaning values. This facilitates the formulation of meaning relations to be defined on the symbolic elements of a lexicon. This specific insight is carried over to the reduction of predicates or predicate concepts in natural language to the minimal form they can assume. This minimal form is formulated in terms of meaning relations in a manner that all complex predicates or predicate concepts can be reduced to a sort of normal form defined by meaning relations. © 2022 Instituto Politecnico Nacional. All rights reserved.

Computacion y Sistemas

Predicate Concepts and their Normal Form

The biological foundations of language reflect assumptions about the way language and biology relate to one another, and with the rise of biological studies of language, we appear to have come closer to a deep understanding of linguistic cognition–the part of cognition constituted by language. This article argues that relations of neurobiological and genetic instantiation between linguistic cognition and the underlying biological substrate are ultimately irrelevant to understanding the higher-level structure and form of language. Linguistic patterns and those that make up the character of cognition constituted by language do not simply arise from the biological substrate because higher-level structures typically assume forms based on constraints that only emerge once these new levels are constructed. The goal is not to show how the mapping problem between linguistic cognition and neurobiology can be solved. Rather, the goal is to show the mapping problem ceases to exist once a different understanding of language-(neuro)biology relations is embraced. With this goal, this article first uncovers a number of logical and conceptual fallacies in strategies deployed in understanding language-(neuro)biology relations. After having shown these flaws, the article offers an alternative view of language-biology relations that shows how biological constraints shape language (nature and form), making it what it is. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Integrative Psychological and Behavioral Science

A Critical Perspective on the (Neuro)biological Foundations of Language and Linguistic Cognition

Natural language meaning has properties of both (embodied) cognitive representations and formal/mathematical structures. But it is not clear how they actually relate to one another. This article argues that how properties of cognitive representations and formal/mathematical structures of natural language meaning can be united remains one of the puzzles in cognitive science. That is primarily because formal/mathematical structures of natural language meaning are abstract, logical, and truth-conditional properties, whereas cognitive/conceptual representations are embodied and grounded in sensory-motor systems. After reviewing the current progress, this work offers, in outline, the general formulations that show how these two different kinds of representations for semantic structures can (potentially) be unified and also proposes three desiderata for testing, in brain dynamics, the mathematical equivalence between formal symbolic representations (and their transitions), and neuronal population codes (and their transitions). © 2022 Cognitive Science Society LLC.

Cognitive Science

The Puzzling Chasm Between Cognitive Representations and Formal Structures of Linguistic Meanings

This article will present a critique of the neurocentric view of language and cognition by locating it within the context of unification in cognitive science. While unity consists in the integration of the constraints, contents, and operations of various levels or scales of organization of the cognitive system, it contrasts with disunity. Disunity emanates from variations in structure and content at any level of the cognitive system that gives rise to significant and often unique differences in experience, appearance, form, and organiza-tion of a cognitive phenomenon at the given level. This happens when the given level is looked at in greater detail. For instance, the gap in the organizational character between a cognitive schema for reasoning how and whether to travel and its account in terms of neuronal activation patterns reflects disunity. Many neurobiological accounts of language aim at the integration of the cognitive organization of language with the neuronal structures at bottom in order to achieve unity, but disunity arises from the special nature of the symbolic/cognitive properties of natural language which are argued to reside neither in the brain nor in the environment alone most plausibly because they are emergent patterns between designated brain states and various kinds of linguistic experience. The proposal that is advanced and then defended with special reference to language–biology relations employs Haugeland’s (Behavioral and Brain Sciences, 1978, 1, 215) notion of dimensions and levels, and thereby emphasizes that unity and disunity can coexist in an explanatory union but from different perspectives and orientations © 2021 American Psychological Association

Journal of Theoretical and Philosophical Psychology

Disunity With Unity in Cognition Within the Context of Language–Biology Relations

This paper revisits the conception of intelligence and understanding as embodied in the Turing Test. It argues that a simple system of meaning relations drawn from words/lexical items in a natural language and framed in terms of syntax-free relations in linguistic texts can help ground linguistic inferences in a manner that can be taken to be 'understanding' in a mechanized system. Understanding in this case is a matter of running through the relevant inferences meaning relations allow for, and some of these inferences are plain deductions and some can serve to act as abductions. Understanding in terms of meaning relations also supervenes on linguistic syntax because such understanding cannot be simply reduced to syntactic relations. The current approach to meaning and understanding thus shows that this is one way, if not the only way, of (re)framing Alan Turing's original insight into the nature of thinking in computing systems. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature.

Axiomathes

Meaning Relations, Syntax, and Understanding

The objective of this study is to investigate facets of the human phonological system in an attempt to elucidate the special nature of mental representations and operations underlying some of the errors in speech sound disorders (SSDs). After examining different theories on the mental representations of sounds and their organization in SSDs, we arrive at the conclusion that the existing elucidations on the phonological representations do not suffice to explain some distinctive facets of SSDs. Here, we endorse a hypothesis in favor of representationalism but offer an alternative conceptualization of the phonological representations (PR). We argue that the PR is to be understood in terms of a phonological base that holds information about a segment’s acoustic structure, and which interacts with other levels in the speech sound system in the mind so as to produce a certain sound. We also propose that the PR is connected to an interface module which mediates interactions between the PR and the articulatory system (AS) responsible for the physical manifestation of speech sounds in real time by way of the coordination of activities of speech organs in the vocal tract. We specifically consider different stages of operations within the interface, a specialized system within the cognitive system, which can explain patterns in the SSD data that have so far remained elusive. Positioned between the PR and the AS, the interface module is the heart of the current study. The presence of an interface module is necessitated by the fact that not all errors of SSDs are explainable in terms of structural, motor or even the symbolic misrepresentations at the level of PR. The interface acts as a mediating system mapping sound representations onto articulatory instructions for the actual production of sounds. The interface module can receive, process, and share the phonological inputs with other levels within the speech sound system. We believe an interface module such as ours holds the key to explaining at least certain speech disarticulations in SSDs. © 2021, The Author(s).

World University root node

Humanities and Social Sciences Communications

The mental representation of sounds in speech sound disorders

The Limits of Language-Thought Influences Can Be Set by the Constraints of Embodiment

This paper will focus on linguistic constructions involving intensional emotive predicates in order to assess the computational complexity of such constructions based on the features of intensional elements in such constructions. It will be first shown that linguistic constructions vary as a function of the nature of intensional elements involved in such constructions. The important insights derived from these facts will be then carried forward for an exploration of the computational complexity of intensional emotive constructions which can be seen to co-vary in complexity scales with the number of intensional elements or features of intensional elements. Possible ramifications emanating from this for the cognitive tractability of semantic contents and for natural language processing will be offered at the end of the paper. © 2021 World Scientific Publishing Company.

New Mathematics and Natural Computation

Computational Complexity of Intensional Emotive Constructions, (In)tractability and Natural Language Processing

This paper approaches the question of how to describe the higher-level internal structures and representations of cognitive systems across various kinds of nonhuman (neuro)cognitive systems. While much research in cognitive (neuro)science and comparative cognition is dedicated to the exploration of the (neuro)cognitive mechanisms and processes with a focus on brain-behavior relations across different non-human species, not much has been done to connect (neuro)cognitive mechanisms and processes and the associated behaviors to plausible higher-level structures and representations of distinct kinds of cognitive systems in non-humans. Although the study of (neuro)cognitive mechanisms and processes can certainly be revealing, (neuro)cognitive mechanisms and processes are underspecified with respect to internal structures and representations of non-human cognitive systems because multiple such mechanisms can target, or be mapped onto, the same internal structure or vice versa. This paper outlines a biosemiotic approach to this linking problem in order to bridge the gap between functions of (neuro)cognitive systems in different species and the higher-level cognitive structures and representations. It is contended that the higher-level internal structures and representations of various cognitive systems are biosemiotic constraints on the (biological) functions of (neuro)cognitive systems that serve to restrict the range of functions (neuro)cognitive systems have or are selected for. This turns out to have implications for issues on the convergent evolution of cognitive traits. © 2020, Springer Nature B.V.

Biosemiotics

Mental Structures as Biosemiotic Constraints on the Functions of Non-human (Neuro)Cognitive Systems

This paper aims to characterize the relationship between information as defined in the information-theoretic approach and linguistic meaning by way of formulation of computations over the lexicon of a natural language. Information in its information theoretic sense is supposed not to be equivalent to linguistic meaning, whereas linguistic meaning has an intrinsic connection to information as far as the form and structure of the lexicon of a language (in a non-lexicological sense) is concerned. We argue that these two apparently conflicting aspects of the relationship between information and linguistic meaning can be unified by showing that information conserves linguistic meaning, only insofar as computations of a certain kind are defined on the symbolic elements of a lexicon. This has consequences not merely for the nature of lexical learning - natural or artificial or otherwise - but also for the conservation of information in axiomatic systems. © 2019 John Benjamins Publishing Company. All rights reserved.

Pragmatics and Cognition

How linguistic meaning harmonizes with information through meaning conservation

This paper proposes a fresh formulation of conceptually grounded meaning relations by way of construction of certain well-defined relations over the lexicon of a natural language. These relations are constrained by the logical structures of linguistic meanings across sentence and discourse contexts. One of the biggest advantages of such meaning relations is that they are not defined over, or do not ride on, the syntactic structure of a given language. Nor do they turn on compositional relations for the computation of meaning values. This helps in the formulation of meaning relations to be defined on the symbolic elements of a lexicon on the one hand, and to be extracted from the surface structure of linguistic constructions on the other. This has consequences not merely for the nature of lexical meaning but also for the construction of a kind of (shallow) semantic networks that can be used for semantic processing in natural language understanding or machine translation systems that are driven by a kind of shallow processing of linguistic meanings. Thus, this paper aims to show the usefulness of a kind of conceptually based characterization of linguistic meaning for its relevance to computational language processing. © 2018 CEUR-WS. All rights reserved.

CEUR Workshop Proceedings

Lexicon, meaning relations, and semantic networks

This book examines linguistic expressions of emotion in intensional contexts and offers a formally elegant account of the relationship between language and emotion. The author presents a compelling case for the view that there exist, contrary to popular belief, logical universals at the intersection of language and emotive content. This book shows that emotive structures in the mind that are widely assumed to be not only subjectively or socio-culturally variable but also irrelevant to a general theory of cognition offer an unusually suitable ground for a formal theory of emotive representations, allowing for surprising logical and cognitive consequences for a theory of cognition. Challenging mainstream assumptions in cognitive science and in linguistics, this book will appeal to linguists, philosophers of the mind, linguistic anthropologists, psychologists and cognitive scientists of all persuasions. © The Editor(s) (if applicable) and The Author(s) 2016.

Language and Cognitive Structures of Emotion

Language and cognitive structures of emotion

This paper seeks to understand machine cognition. The nature of machine cognition has been shrouded in incomprehensibility. We have often encountered familiar arguments in cognitive science that human cognition is still faintly understood. This paper will argue that machine cognition is far less understood than even human cognition despite the fact that a lot about computer architecture and computational operations is known. Even if there have been putative claims about the transparency of the notion of machine computations, these claims do not hold out in unraveling machine cognition, let alone machine consciousness (if there is any such thing). The nature and form of machine cognition remains further confused also because of attempts to explain human cognition in terms of computation and to model/simulate (aspects of) human cognitive processing in machines. Given that these problems in characterizing machine cognition persist, a view of machine cognition that aims to avoid these problems is outlined. The argument that is advanced is that something becomes a computation in machines only when a human interprets it, which is a kind of semiotic causation. From this it follows that a computing machine is not engaged in a computation unless a human interprets what it is doing; instead, it is engaged in machine cognition, which is defined as a member or subset of the set of all possible mappings of inputs to outputs. The human interpretation, which is a semiotic process, gives meaning to what a machine does, and then what it does becomes a computation. © 2013 Springer Science+Business Media Dordrecht.

Does Computation Reveal Machine Cognition?

This book explores how and in what ways the relationship between language, mind and computation can be conceived of, given that a number of foundational assumptions about this relationship remain unacknowledged in mainstream linguistic theory, yet continue to be the basis of theoretical developments and empirical advances. © Prakash Mondal 2014. All rights reserved.

Language, Mind and Computation

Language, mind and computation

This paper explores the link between rules of grammar, grammar formalisms and the architecture of the language faculty. In doing so, it provides a flexible meta-level theory of the language faculty through the postulation of general axioms that govern the interaction of different components of grammar. The idea is simply that such an abstract formulation allows us to view the structure of the language faculty independently of specific theoretical frameworks/formalisms. It turns out that the system of rules, axioms and constraints of grammar cannot be explicitly represented in a general architecture of the language faculty -which circumvents the ontological mismatch of mental representations and formal/ axiomatic properties of language. Rather, the system of rules, axioms, constraints of grammar is intentionally projected by humans, and this projection realizes/instantiates what Dascal (1992) calls 'psychopragmatics'. Relevant implications for linguistic theory, learnability and (computational) models of language processing are also explored. © John Benjamins Publishing Company.

How does the faculty of language relate to rules, axioms, and constraints?

This paper aims at pointing out a range of differences between logical form as used in logic and logical form (LF) as used in the minimalist architecture of language. The differences will be shown from different angles based on the ways in which they differ in form and represent some natural language phenomena. The implications as following on from such differences will be then linked to the issue of whether semantic realization in mind/brain is computational. It will be shown that the differences between logical form as used in logic and logical form (LF) as used in the minimalist architecture of language will help us latch on to the realization that there is no determinate way in which semantics can be computational or computationally realized. © 2013 Springer-Verlag.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Logical form vs. logical form: How does the difference matter for semantic computationality?

In this paper a connection between inthentionality, inthensionality, language and emotion will be drawn up terough a demonstration of an intimathe relationship between the inthentionality of emotion and inthensionality in language. What will be shown is that the inthentionality of emotion can ultimathely be traced to the inthensionality of emotional conthexts. For this purpose, emotive predicathes will be cathegorized in therms of their inthensional behavior and regularities. They will then be brought forward for an explication of why and how far the inthentionality of emotion is unique. The insights derived from the relevant analyses will then be employed for the implications and ramifications that might be terown upon the fabric of emotion and language within the space of cognition. © John Benjamins Publishing Company.