Grammar Representation Research Articles

Time-resolved brain activation patterns reveal hierarchical representations of scene grammar when viewing isolated objects

Time-resolved brain activation patterns reveal hierarchical representations of scene grammar when viewing isolated objects

Dialect separation and cross-dialectal influence: a study on the grammatical gender of Oromo

Abstract The extent to which the grammar of one dialect influences the grammar of another and the mechanisms that bidialectal speakers employ to distinguish a target grammar from non-target grammar have not been adequately investigated. In this study, we elucidate these issues by investigating the grammatical gender of Oromo, a Cushitic language that is spoken in Ethiopia. The results from two successive offline experiments indicate that Oromo bidialectal speakers can differentiate between the grammar of their native dialect and that of a non-native dialect in both spoken and written modes. This finding implies the existence of a dual-system representation of grammar. Moreover, there is a significant amount of dialect mixing that varies across various developmental stages and modalities. The bidialectal speakers’ ability to differentiate between the grammar of their native dialect and that of a non-native dialect is constrained by the magnitude of their exposure to the non-native dialect, modalities, and a specific property of grammatical forms. Here, we propose an interactive dialect separation model that accounts for diverse dialect contexts.

Bilectal Exposure Modulates Neural Signatures to Conflicting Grammatical Properties: Norway as a Natural Laboratory

AbstractThe current study investigated gender (control) and number (target) agreement processing in Northern and non‐Northern Norwegians living in Northern Norway. Participants varied in exposure to Northern Norwegian (NN) dialect(s), where number marking differs from most other Norwegian dialects. In a comprehension task involving reading NN dialect writing, P600 effects for number agreement were significantly affected by NN exposure. The more exposure the NN nonnatives had, the larger the P600 was, driven by the presence of number agreement (ungrammatical in NN). In contrast, less exposure correlated to the inverse: P600 driven by the absence of number agreement (ungrammatical in most other dialects). The NN natives showed P600 driven by the presence of number agreement regardless of exposure. These findings suggests that bilectalism entails the representation of distinct mental grammars for each dialect. However, like all instances of bilingualism, bilectalism exists on a continuum whereby linguistic processing is modulated by linguistic experience.

УДАРЕНИЕТО НА СЪЩЕСТВИТЕЛНИТЕ И ПРИЛАГАТЕЛНИТЕ ИМЕНА, ОБРАЗУВАНИ С ПРЕДСТАВКИТЕ ВЪЗ-, ИЗВЪН-, НЕ-, ПРА-, ПРЕ-

This notice deals with the stress in nouns and adjectives formed with the prefixes въз-, извън-, не-, пра-, пре- and its representation in the Academic Grammar and the Official Spelling Dictionary from 2012. After laying out the principles used to define whether a word bears one or two stresses, the author points out the issues in representing the stress of the studied words.

Discourse markers within sentence grammar: Further evidence from ʕaad in Jordanian Arabic

This article investigates the discourse functions of ʕaad in Jordanian Arabic (JA), based on a naturally occurring corpus which consists of 20 sociolinguistic interviews with 60 participants. Upon analysing all occurrences of ʕaad in the corpus, we propose that ʕaad is a discourse marker that provides supplementary information that relates the speaker's attitude (i.e., disagreement) to the proposition expressed by the host sentence. Additionally, this article offers a syntactic account of this discourse marker arguing that its distribution (and interpolation) can be syntactically captured. The syntactic analysis is based on the notion of grounding (Wiltschko and Heim, 2016; Thoma, 2016; Wiltschko, 2017a, 2017b). We essentially argue that the marker ʕaad heads the so-called Speaker-oriented Ground Phrase, following its main function in expressing the commitment that the speaker displays towards the proposition rather than asking the addressee for a request of how to respond to the utterance. In so doing, this article adds credence to proposals under which discourse markers can be incorporated within sentence grammar with no need for an extra level of grammar representation (see Potts, 2005; de Vries, 2012; Wiltschko and Heim, 2016).

On embedding Lambek calculus into commutative categorial grammars

AbstractWe consider tensor grammars, which are an example of ‘commutative’ grammars, based on the classical (rather than intuitionistic) linear logic. They can be seen as a surface representation of abstract categorial grammars (ACG) in the sense that derivations of ACG translate to derivations of tensor grammars and this translation is isomorphic on the level of string languages. The basic ingredients are tensor terms, which can be seen as encoding and generalizing proof nets. Using tensor terms makes the syntax extremely simple and a direct geometric meaning becomes transparent. Then we address the problem of encoding noncommutative operations in our setting. This turns out possible after enriching the system with new unary operators. The resulting system allows representing both ACG and Lambek grammars as conservative fragments, while the formalism remains, as it seems to us, rather simple and intuitive.

The measurement, evolution, and neural representation of action grammars of human behavior

Human behaviors from toolmaking to language are thought to rely on a uniquely evolved capacity for hierarchical action sequencing. Testing this idea will require objective, generalizable methods for measuring the structural complexity of real-world behavior. Here we present a data-driven approach for extracting action grammars from basic ethograms, exemplified with respect to the evolutionarily relevant behavior of stone toolmaking. We analyzed sequences from the experimental replication of ~ 2.5 Mya Oldowan vs. ~ 0.5 Mya Acheulean tools, finding that, while using the same “alphabet” of elementary actions, Acheulean sequences are quantifiably more complex and Oldowan grammars are a subset of Acheulean grammars. We illustrate the utility of our complexity measures by re-analyzing data from an fMRI study of stone toolmaking to identify brain responses to structural complexity. Beyond specific implications regarding the co-evolution of language and technology, this exercise illustrates the general applicability of our method to investigate naturalistic human behavior and cognition.

Resumptive pronouns facilitate processing of long-distance relative clause dependencies in second language English

This study provides evidence that resumptive pronouns (RPs) can facilitate the processing of long-distance subject relative clause (RC) dependencies during second language (L2) sentence comprehension, even where they are disallowed in both the first language (L1) and the target language. A test group of 29 L1-Korean L2 learners (L2ers) of English and a control group of 25 native English speakers completed an online self-paced reading task (SPRT) and an offline acceptability judgment task (AJT) designed to test whether RPs reflect Interlanguage grammar representations and/or a strategy to alleviate processing overload. Analysis of the SPRT data from both response times and comprehension question accuracy indicates that RPs assisted the L2ers, but not the native speakers, with dependency resolution in long-distance RCs. For the AJT data, a proficiency effect was observed whereby some lower-proficiency L2ers, but not the higher-proficiency ones or the native speakers, tended to prefer RPs over gaps in long-distance RCs. The implications of these findings and plans for future research are discussed.

Description Of Context Free Grammars In Json Format For Parser Generators

Analysis of various presentations for context free grammars provided with parser generators. A new description format of context free grammars is proposed. Given a representation of context free grammar in JSON format. The concept of a new parser generator based on JSON data format of describing context free grammars is presented. Described a parser generation scheme based on that concept.

A Tree Adjoining Grammar representation for models of stochastic dynamical systems

Model structure and complexity selection remains a challenging problem in system identification, especially for parametric non-linear models. Many Evolutionary Algorithm (EA) based methods have been proposed in the literature for estimating model structure and complexity. In most cases, the proposed methods are devised for estimating structure and complexity within a specified model class and hence these methods do not extend to other model structures without significant changes. In this paper, we propose a Tree Adjoining Grammar (TAG) for stochastic parametric models. TAGs can be used to generate models in an EA framework while imposing desirable structural constraints and incorporating prior knowledge. In this paper, we propose a TAG that can systematically generate models ranging from FIRs to polynomial NARMAX models. Furthermore, we demonstrate that TAGs can be easily extended to more general model classes, such as the non-linear Box–Jenkins model class, enabling the realization of flexible and automatic model structure and complexity selection via EA.

Real Time Speech To Text Text To Speech Converter With Automatic Text Summarizer using Natural Language Generation And Abstract Meaning Representation

Due to extensive needs for growth in various sectors, which include software, telecom, healthcare, defence, etc., there is a necessary increase in the number as well as the duration of meetings, conference calls, reconnaissance stakeouts, financial reviews. The obtained reports of these play a significant role in defining the plan of actions. The proposed model is to convert real-time speech to corresponding text and then to its respective summary using Natural Language Grammar (NLG) and Abstract Meaning Representation (AMR) graphs and then again turned back the obtained summary to speech. The proposed model intends to achieve the task using two major algorithms, 1) Deep Speech 2, 2) AMR graphs. The speech-recognition model recommended has a speedup of 4x if the algorithm runs on a Central Processing Unit (CPU), and the use of particular Graphics Processing Units (GPUs) for running deep learning algorithms can give a speedup of 21x. The performance of the summarizer used is close to the Lead-3-AMR-Baseline model, which is a solid baseline for the CNN/Dailymail dataset. The summarizer we use scores ROGUE score close to the Lead-3- AMR-Baseline model with an accuracy of 99.37%.

Word Frequency Is a Cue to Lexical Category for 8-Month-Old Infants.

The linguistic distinction between function words (functors) (e.g., the, he, that, on…), signaling grammatical structure, and content words (e.g., house, blue, carry…), carrying meaning, is universal across the languages of the world. These two lexical categories also differ in their phonological makeup (functors being shorter and more minimal) and frequency of occurrence (individual functors being much more frequent than most content words). The frequency-based discrimination of the two categories could constitute a powerful mechanism for infants to acquire the basic building blocks of language. As functors constitute closed classes and content words come in open classes, we examined whether 8-month-old monolingual infants relied on word frequency to categorize and track functors and content words. In six artificial grammar-learning experiments, we have found that infants process frequent words as belonging to closed classes, and infrequent words as belonging to open classes, and they map the relative order of these categories following the basic word order of their native language. These findings provide the earliest evidence that infants use word frequency as a cue to lexical categories and combine them to build rudimentary representations of grammar.

Word Frequency is a Cue to Lexical Category at 8 Months

The distinction between function words, signalling grammatical structure, and content words, carrying meaning, is universal. The two lexical categories also differ in their phonological makeup and frequency of occurrence. Thus, their frequency-based discrimination could constitute a powerful initial mechanism for infants to acquire the basic building blocks of language. As functors constitute closed classes, while content words come in open classes, we examined whether 8-month-old monolingual infants relied on word frequency to categorize and track functors and content words. In four artificial grammar-learning experiments we have found that infants treat frequent words as belonging to closed classes, and infrequent words as belonging to open classes and they map the relative order of these categories following the basic word order of their native language. These findings provide the earliest evidence that infants use word frequency as a cue to lexical categories and combine them to build rudimentary representations of grammar.

Studying language and linguistics through a plurilingual lens

While scholarship about language has had a monolingual bias for much of its recent history, this paper represents an initial attempt to shift the study of language and linguistics to a plurilingual lens. That is, past and current scholars assume that the global default is monolingualism and frame their hypotheses and theories from that monolingual worldview, yet bilingualism and plurilingualism are widespread and becoming more common with the global movement in acquiring English. This article attempts to take the first steps in addressing the gap of a plurilinguistic perspective in research and other scholarship by reframing linguistic questions as viewed though a plurilingual lens regardless of the theoretical framework. What can we learn from research both within our field and from other disciplines on bilinguals and plurilinguals regarding what human language is? For example, taking plurilingual as the norm necessitates treating translanguaging, code switching, and code stumbling as basic language use. How does a plurilingual lens affect our representation of grammar(s)? How does it affect our notions of language? Finally, how does it affect our understanding of the human capacity for acquiring languages?

On (the) sandhi between the Sanskrit and the Modern Western Grammatical Traditions: From Colebrooke to Bloomfield via Müller

This article traces the history of how modern Western linguistics adopted the term sandhi from the Sanskrit grammatical tradition and adapted it to its theoretical needs. In particular, we will acknowledge the fundamental role played by Muller, 1 who combining both Indic (Prakriyā grammars and Prātiśākhyas) and Western approaches (those of Colebrooke and Bopp) to the representation of Sanskrit grammar, coined in 1866 the labels of internal sandhi and external sandhi. Such labels gained momentum thanks to the works of Whitney in the 19th century and Bloomfield in the 20th century and eventually became common parlance in Western linguistics.

On Transforming Narrowing Trees into Regular Tree Grammars Generating Ranges of Substitutions

The grammar representation of a narrowing tree for a syntactically deterministic conditional term rewriting system and a pair of terms is a regular tree grammar that generates expressions for substitutions obtained by all possible innermost-narrowing derivations that start with the pair and end with particular non-narrowable terms. In this paper, under a certain syntactic condition, we show a transformation of the grammar representation of a narrowing tree into another regular tree grammar that overapproximately generates the ranges of ground substitutions generated by the grammar representation. In our previous work, such a transformation is restricted to the ranges w.r.t. a given single variable, and thus, the usefulness is limited. We extend the previous transformation by representing the range of a ground substitution as a tuple of terms, which is obtained by the coding for finite trees. We show a precise definition of the transformation and prove that the language of the transformed regular tree grammar is an overapproximation of the ranges of ground substitutions generated by the grammar representation. We leave an experiment to evaluate the usefulness of the transformation as future work.

THE VIRGIN MARY AS LADY GRAMMAR IN THE MEDIEVAL WEST

The Virgin Mary, as Mother of the Word, has long been associated with early literacy training in the medieval West, an association that, as this article argues, connects her to The Marriage of Philology and Mercury's Lady Grammar. While Gary P. Cestaro has demonstrated the ways in which representations of Lady Grammar became more maternal throughout the medieval period, this article demonstrates how and why the Virgin Mother took on the persona of Lady Grammar in both verbal and material arts from the High to the Late Middle Ages. It explores the famous sculptures of the Virgin and Lady Grammar on the Royal Portal at Chartres Cathedral, the writings of grammatical theorists that led to these depictions, and the thirteenth-century artes poetriae that portray Mary as a Christian Grammatica. From St. Augustine's declaration that grammar is a “guardian” to the claims of Gervais of Melkley, John of Garland, and Eberhard the German that Mary is the mother of beautiful expressions, grammatical thought and practice in the medieval West led to a characterization of the Virgin, guardian of the Word in her womb and parent to Wisdom, as the supreme teacher and exemplar of Latin. Adopting Lady Grammar's iconography of the nourishing breast, classroom text, and punitive whip, the Virgin Mary is not only connected to basic Latin instruction but also comes to embody its principles.

First love simplicity: A systemic-functional perspective study of Karina Del Campo�s Do You Remember Our Love?

The current study aims at exploring the intended meaning and structure of a poem entitled �Do You Remember Our Love?� written by a poet, ��Karina Del Campo (2009) in both interpretational and systemic functional perspectives. In the former, the poem was examined interpretatively in order to find out the possible stance of the poet; meanwhile the later was an analytical representation of systemic functional grammar in the framework of construing the three domains of meanings: ideational, interpersonal and textual in order to arrive at the field, the tenor and the mode of the discourse.� It turns out that the poem is �a reflection of a woman�s feeling (the poet�s) toward her ex-boyfriend�finely described in a repeated style of the major clause, supported and elaborated in several minor clauses. The poet tries very hard to ignite her ex-boyfriend�s love memories with her and to possibly invite him to reunite even though it seems to be a mission impossible. The poem has both social and psychological impacts on the poet herself and the readers in a wider scope.

The Influence of Context on the Learning of Metrical Stress Systems Using Finite-State Machines

Languages vary in the way stress is assigned to syllables within words. This article investigates the learnability of stress systems in a wide range of languages. The stress systems can be described using finite-state automata with symbols indicating levels of stress (primary, secondary, or no stress). Finite-state automata have been the focus of research in the area of grammatical inference for some time now. It has been shown that finite-state machines are learnable from examples using state-merging. One such approach, which aims to learn k-testable languages, has been applied to stress systems with some success. The family of k-testable languages has been shown to be efficiently learnable (in polynomial time). Here, we extend this approach to k, l-local languages by taking not only left context, but also right context, into account. We consider empirical results testing the performance of our learner using various amounts of context (corresponding to varying definitions of phonological locality). Our results show that our approach of learning stress patterns using state-merging is more reliant on left context than on right context. Additionally, some stress systems fail to be learned by our learner using either the left-context k-testable or the left-and-right-context k, l-local learning system. A more complex merging strategy, and hence grammar representation, is required for these stress systems.

Modern Standard Arabic Grammar Automatic Extraction from Penn 1 Arabic Treebank Using Natural Language Toolkit

This paper presents a methodology for rule based bottom up parsing technique forModern Standard Arabic (MSA) inContext Free Grammar (CFG) formalism in Phrase Structure Grammar (PSG) representation, where the grammar isautomatically extracted from a syntactically annotated corpus.The extracted grammar is used to build an automatic lexicon andgrammar rules module. Furthermore, the extracted CFG is further transformed into Probabilistic Context Free Grammar (PCFG)that could be used in a hybrid approach, which is also calculated automatically. The used corpus is the Penn ArabicTreebank(PATB)and algorithm implementation is performed with Natural Language Processing Toolkit (NLTK).The parsershowed that automatic extraction of grammar improved the grammar building phase in both coverage of structures and timeneeded, but still needs further manual constrains addition. Automatic extraction of grammar is able to enhance rule basedgrammar parsers and it will enable a new paradigm of statistically directed symbolic parsing.