Phrasal Context Research Articles

Vertical larynx actions and intergestural timing stability in Hausa ejectives and implosives.

The current project undertakes a kinematic examination of vertical larynx actions and intergestural timing stability within multi-gesture complex segments such as ejectives and implosives that may possess specific temporal goals critical to their articulatory realization. Using real-time MRI (rtMRI) speech production data from Hausa non-pulmonic and pulmonic consonants, this study illuminates speech timing between oral constriction and vertical larynx actions within segments and the role this intergestural timing plays in realizing phonological contrasts and processes in varying prosodic contexts. Results suggest that vertical larynx actions have greater magnitude in the production of ejectives compared to their pulmonic counterparts, but implosives and pulmonic consonants are differentiated not by vertical larynx magnitude but by the intergestural timing patterns between their oral and vertical larynx gestures. Moreover, intergestural timing stability/variability between oral and non-oral (vertical larynx) actions differ among ejectives, implosives, and pulmonic consonants, with ejectives having the most stable temporal lags, followed by implosives and pulmonic consonants, respectively. Lastly, the findings show how contrastive linguistic 'molecules'- here, segment-sized phonological complexes with multiple gestures- interact with phrasal context in speech in such a way that it variably shapes temporal organization between participating gestures as well as respecting stability in relative timing between such gestures comprising a segment.

Morphosyntactic prediction in automatic neural processing of spoken language: EEG evidence

Automatic parsing of syntactic information by the human brain is a well-established phenomenon, but its mechanisms remain poorly understood. Its best-known neurophysiological reflection is the so-called early left-anterior negativity (ELAN) component of event-related potentials (ERPs), with two alternative hypotheses for its origin: (1) error detection, or (2) morphosyntactic prediction/priming. To test these alternatives, we conducted two experiments using a non-attend passive design with visual distraction and recorded ERPs to spoken pronoun-verb phrases with/without agreement violations and to the same critical verbs presented in isolation without preceding pronouns. The results revealed an ELAN at ∼130-220 ms for pronoun-verb gender agreement violations, confirming a high degree of automaticity in early morphosyntactic parsing. Critically, the strongest ELAN was elicited by verbs outside phrasal context, which suggests that the typical ELAN pattern is underpinned by a reduction of ERP amplitudes for felicitous combinations, reflecting syntactic priming/predictability between related words/morphemes (potentially mediated by associative links formed during previous linguistic experience) rather than specialised error-detection processes.

What Fires Together, Wires Together: The Effect of Idiomatic Co-Occurrence on Lexical Networks

This study investigated the processing of lexical elements of idioms in isolation. Using visual word priming, spreading activation for idiomatically related word pairs (e.g., pop–question) was compared to that for semantically related (e.g., answer–question) and unrelated word pairs (e.g., trim–question) in two experiments varying in SOA (500 ms and 350 ms). In line with hybrid theories of idiom representation and processing, facilitatory priming was found in both experiments for idiomatic primes, suggesting a tight link between the words of an idiom that is mediated by a common idiom representation. While idiomatic priming was stable across SOAs, semantic priming was stronger for the short SOA, implying fast and early activation. In conclusion, one lexical element of an idiom can facilitate the processing of another, even if the elements are not presented within a phrasal context (i.e., within an idiom), and without the words being semantically related. We discuss our findings in light of theories about idiom processing, as well as current findings in the field of semantic priming.

STRUCTURAL SYNTACTIC ANALYSIS OF NOUN PHRASES IN INDONESIAN

Syntax is a part of linguistics that studies how words are combined into sentences and phrases. In this study, we focus on analyzing the syntax of noun phrases in Indonesian. We use the treebank analysis technique to identify the syntactic structure of noun phrases in Indonesian. Study results show that noun phrases in Indonesian have complex and varied syntactic structures and that the context and types of noun phrases play an important role in influencing the syntactic structure of noun phrases. These findings are important for understanding how noun phrases are formed and understood in Indonesian and how it affects language processing.

Conditional Knowledge Extraction Using Contextual Information Enhancement

Conditional phrases provide fine-grained domain knowledge in various industries, including medicine, manufacturing, and others. Most existing knowledge extraction research focuses on mining triplets with entities and relations and treats that triplet knowledge as plain facts without considering the conditional modality of such facts. We argue that such approaches are insufficient in building knowledge-based decision support systems in vertical domains, where specific and professional instructions on what facts apply under given circumstances are indispensable. To address this issue, this paper proposes a condition-aware knowledge extraction method using contextual information. In particular, this paper first fine-tunes the pre-training model to leverage a local context enhancement to capture the positional context of conditional phrases; then, a sentence-level context enhancement is used to integrate sentence semantics; finally, the correspondences between conditional phrases and relation triplets are extracted using syntactic attention. Experimental results on public and proprietary datasets show that our model can successfully retrieve conditional phrases with relevant triplets while improving the accuracy of the matching task by 2.68%, compared to the baseline.

Disentangling word stress and phrasal prosody: A view from Georgian

This paper investigates the interaction of word stress and phrasal prosody in Georgian by studying the distribution of acoustic cues (duration, intensity, F0) in controlled data. The results show that initial syllables in Georgian words are marked by greater duration than all subsequent syllables, regardless of syllable count and phrasal context. After excluding domain-initial strengthening as an alternative explanation, this finding provides evidence in favor of fixed initial stress. Likewise, initial syllables are marked by greatest intensity, but the consistent gradual drop in intensity throughout the word suggests that this effect may not be stress-related. The F0 results align with the existing accounts: individual lexical words form ACCENTUAL PHRASES, marked by a low pitch accent on the initial syllable and a high final boundary tone on the final syllable. Additionally, new evidence for a phrasal accent, aligned with the penult, is presented. F0 targets are shown to be completely absent in the context of post-focal deaccenting, which shows that F0-marking in Georgian is reserved for phrasal prosody and is not intrinsic to stress-marking. These results help account for the facts related to word stress, phrasal intonation, and their interplay in Georgian, the object of debate in the literature.

Basic Reporting Verbs as Markers of the Author’s Idiostlyle

This article reveals the peculiarities of idiostyles referring to works by nineteenth-century classical Russian writers (F. M. Dostoevsky, L. N. Tolstoy, A. P. Chekhov, and I. S. Turgenev). Based on intertext and inter-style statistical comparison, the author aims to reveal lexical compatibility and some individual particularities of using some frequent reporting verbs in literary texts belonging to the same period. The research is methodologically based on the ideographic approach to literary text analysis which takes into consideration internal correlations existing between lexical paradigmatics and syntagmatics. Lexical bigrams (pairs of words used in one phrase context) are taken as a unit of comparative lexicostatistical and contextological analysis. Word combinations of this type are used by the same writer in different texts, though they are not found in works by the other authors. The only obligatory element of a lexical bigram is a word which is often used by all the writers in question as it reveals the specific patterns of an author’s work with the same language material (such reporting verbs as сказать (‘say’), спросить (‘ask’), ответить (‘answer’), заметить (‘note’) are very representative for this purpose). So-called “idiostylistic markers” most frequently used to describe the moment of speech are identified for each writer in question. The author draws conclusions about the individual specificity of these stylistic patterns. Author-specific lexical compatibility shows that in the contexts of the verbs in question with lexical bigrams extracted from novels by L. N. Tolstoy, the use of the verb отвечать (‘answer’) prevails and involves an expression of emotions. The verb замечать (‘note’) which is frequently used in novels by F. M. Dostoevsky, reveals psychological perceptional particularities of speech of the other. The author argues that the use of the verb говорить (‘say’) for introducing direct speech is typical of А. P. Chekhov’s idiostyle where it is syntactically combined with adverbial participles denoting various nonspeech actions drawing the reader’s attention to a particular detail. The verb промолвить (‘utter’) is specific for I. S. Turgenev’s idiostyle and reveals implicit but semantically important correlations existing between the concepts of speech, thought, and motion.

The contextual behaviour of specialised collocations: typology and lexicographic treatment

AbstractA corpus-based analysis of specialised phraseology can shed light on the role of phrasal context in terminology. This contribution describes the behaviour of constituents of simple and complex specialised collocations in technical texts and the way in which these are distributed in different contexts ranging from the immediate surroundings of a node to the inclusion of a much larger portion of text. The contextual behaviour of specialised collocations is exemplified by English and Italian terms in the domain of photovoltaic technology. This contribution aims to identify and classify specialised collocations along their formation modalities and contexts, as well as to discuss the impact of these phenomena on their representation in LSP lexicographic resources. Issues and options concerning the extraction of collocations and contexts are also addressed.

The realization of unaccentedness in Korean and Japanese pitch accent systems

In this paper, I discuss how unaccented words are realized in lexical pitch accent varieties of Korean and Japanese, focusing on Daegu/North Gyeongsang Korean. Previous studies such as Kenstowicz & Sohn (1997) and Jun et al. (2006) claim that Daegu Korean lacks an unaccented class. I show that the final-accented class in Daegu Korean proposed by Kenstowicz & Sohn (1997) and Jun et al. (2006) is in fact unaccented, comparing final-accented words in Daegu Korean with unaccented words in Tokyo Japanese in phrasal contexts. Most previous studies examined only the tone interaction between words and clitics to determine the accentedness or unaccentedness of the words, but this study demonstrates that phrasal prosody should also be considered to help identify the accentedness or unaccentedness of words.

Relative Contributions of Social, Contextual, and Lexical Factors in Speech Processing.

This exploratory study examined the simultaneous interactions and relative contributions of bottom-up social information (regional dialect, speaking style), top-down contextual information (semantic predictability), and the internal dynamics of the lexicon (neighborhood density, lexical frequency) to lexical access and word recognition. Cross-modal matching and intelligibility in noise tasks were conducted with a community sample of adults at a local science museum. Each task featured one condition in which keywords were presented in isolation and one condition in which they were presented within a multiword phrase. Lexical processing was slower and more accurate when keywords were presented in their phrasal context, and was both faster and more accurate for auditory stimuli produced in the local Midland dialect. In both tasks, interactions were observed among stimulus dialect, speaking style, semantic predictability, phonological neighborhood density, and lexical frequency. These interactions revealed that bottom-up social information and top-down contextual information contribute more to speech processing than the internal dynamics of the lexicon. Moreover, the relatively stronger bottom-up social effects were observed in both the isolated word and multiword phrase conditions, suggesting that social variation is central to speech processing, even in non-interactive laboratory tasks. At the same time, the specific interactions observed differed between the two experiments, reflecting task-specific demands related to processing time constraints and signal degradation.

Leveraging fusion of sequence tagging models for toxic spans detection

The upsurge of prolific blogging and microblogging platforms enabled the abusers to spread negativity and threats greater than ever. Negative and hateful comments are averting users from sharing their opinion freely on social media platforms. It often breaks people’s confidence and causes extensive damage to their mental health. Hence, identifying these toxic contents and taking appropriate measures against them is crucial to preserve a safe environment on social media. Numerous state-of-the-art approaches classify the whole content as toxic or non-toxic, but they don’t distinguish the precise toxic portion from the whole content. Detecting the toxic portions is essential as it substantially aids to moderate the toxic contents through excluding the abusive parts. This paper describes our proposed approach to detect the toxic portions from text contents efficiently and accurately. We explore an ensemble of sequence labeling models including the word embedding-based Spark NLP NER (named entity recognition) deep learning model, spaCy NER model with custom toxic tags, and ALBERT NER model to identify the toxic spans. The NER-based models usually intend to capture the contextual attributes of phrases and spans that are essential for named entity recognition. As the toxic span detection task also requires us to apprehend the phrasal context for detecting toxic span, the similarity between these two tasks inspires us to exploit these NER models. Finally, we determine the final toxic spans using a prevalence-based fusion of the predictions generated by these models. The fusion strategy enables us to consolidate the diversity of these models for perceiving the phrasal context in all aspects. Experimental results achieved on the SemEval-2021 toxic spans detection dataset depict that our model meticulously captures the toxic fragment and achieves a competitive result among the other state-of-the-art methods.

ВІДОБРАЖЕННЯ ПРОЦЕСУ АНАПЛАЗІЇ ПРИ ФОРМУВАННІ МАЙБУТНЬОГО ЧАСУ ГЕРМАНСЬКИХ МОВ

The purpose of this article is to separate grammatical structures that demonstrate the development of the future tense forms in the Germanic languages. The first step of research includes the identification of word forms for temporal description. Gradual identification of primitive analytical forms gives the possibility of tracing the gradual analytisation of the corresponding word combinations and their further transformation into stable analytical verb structures. Finding out latent features helps to recognize differentiated grammatical forms that are used to create and build the set of the formal Germanic future tense structures. The subject of the research is the components used to form temporal verb forms that project the action into the future. The Gothic language, which is understood as the initial, primary stage for the research, used forms of the present tense to describe the future action involving a phrase or an upper phrase context. Within the present tense forms a prefixal word-formation model was found. The Gothic optative was involved to render the future tense. The weak models of Gothic analytisation are connected with the infinitive phrase and auxiliary verb haban. Combination of auxiliary verbs with verbals (infinitive or participle I) were found in the North and West Germanic languages. These verb combinations involved a very restricted set of notional verbs used in two verbal forms. The first element of the phrase that falls under the process of future grammaticalization was preterite-present verbs, inchoative and some durative verbs. Stability of primary analytical temporal forms was created by using only two variants of verbals (infinitive or participle I). The first component of analytical temporal forms gradually lost its primary lexical meaning through its transformation into the auxiliary element. In the process of further differentiation of the Germanic languages some peculiarities were traced. The German language did not develop individual analytical forms with preterite-present (modal) verbs. Other West Germanic and Scandinavian languages used preterite-present (modal) verbs as a leading mechanism for temporal analytisation. Creation of analytical temporal forms happened within twofold formats.

Neural representation of words within phrases: Temporal evolution of color-adjectives and object-nouns during simple composition.

In language, stored semantic representations of lexical items combine into an infinitude of complex expressions. While the neuroscience of composition has begun to mature, we do not yet understand how the stored representations evolve and morph during composition. New decoding techniques allow us to crack open this very hard question: we can train a model to recognize a representation in one context or time-point and assess its accuracy in another. We combined the decoding approach with magnetoencephalography recorded during a picture naming task to investigate the temporal evolution of noun and adjective representations during speech planning. We tracked semantic representations as they combined into simple two-word phrases, using single words and two-word lists as non-combinatory controls. We found that nouns were generally more decodable than adjectives, suggesting that noun representations were stronger and/or more consistent across trials than those of adjectives. When training and testing across contexts and times, the representations of isolated nouns were recoverable when those nouns were embedded in phrases, but not so if they were embedded in lists. Adjective representations did not show a similar consistency across isolated and phrasal contexts. Noun representations in phrases also sustained over time in a way that was not observed for any other pairing of word class and context. These findings offer a new window into the temporal evolution and context sensitivity of word representations during composition, revealing a clear asymmetry between adjectives and nouns. The impact of phrasal contexts on the decodability of nouns may be due to the nouns' status as head of phrase-an intriguing hypothesis for future research.

МОДЕЛЮВАННЯ АНАЛІТИЧНОГО РОЗВИТКУ ФОРМ ГОТСЬКОГО МАЙБУТНЬОГО ЧАСУ

The purpose of this article is to give the model, which demonstrates the development of the Future tense forms in the Gothic language. The initial stage of modelling the Future tense development includes the description of components according to their constituent features. It gives the possibility of tracing the gradual analytisation of corresponding grammatical form, and finding out latent features, which are characteristic for differentiated grammatical forms creating and building the set of Germanic future tense formal structures. The subject of the investigation are peculiarities of formation mechanism of temporal verb forms for projecting the action into the future. To describe the future action the Gothic language used forms of the Present tense involving phrase or upper phrase context. Within the Present tense forms a prefixal word formation model was found. The Greek future tense was translated involving prefixal and present forms in the Gothic language. The Gothic optative was involved to render the future tense. The present tense forms gain future meaning under the influence of aspect-tense specificity, which is recognized as futurelizing factor. Functions of the aspect-tense specificity may be performed with phrase or upper phrase context and syntactical structures with definitely represented semantics. Distinguished present tense constructions create the primary pivot, which is a basis for further development of the Gothic future tense forms. Gothic analytical structures with participle or infinitive were formed involving inchoative, strong, preterite present verbs. These structures are recognized as compound verbal predicates. Analytical structures cover the pivot creating coaxial cylinders. The whole model may be recognized as divergent-rotational because representing the Gothic future tense forms model itself "moves" along the temporal axis. Multilevel model structure demonstrates the fact that analytical forms are changeable in the gravitation. The comparison of divergent-rotational model components and peculiarities of their arrangement indicates and the caudal development of the Future tense forms in the Gothic language. Tendencies found and distinguished as initial, primary in the Gothic language happen in the process of development of the Old Germanic languages. These tendencies are reflected in the Modern Germanic languages, too.

Authorial compatibility of words in I.A. Goncharov’s novels: 
 comparative stylometry

The following article deals with peculiarities of unique lexical compatibility in classical prose of the XIX century and contains preliminary results of the cross-disciplinary corpus research performed by group of scientists of the Ural Federal University. This project suggests creation of individual syntagmatic profiles for the famous Russian writers. With works of I.A. Goncharov as an example and compared to the texts of other authors special context surrounding for words zhizn (life) and zhit (live) is systematized. Initial material is extracted through comparative statistical analysis of bigrams lexical pairs, when used in the same phrase context. Lexems zhizn (life) and zhit (live) are one of the most frequent words in Russian language, however, each author tends to use them in his own, special context surrounding. Novels by I.A. Goncharov (A Common Story, Oblomov, The Precipice, Frigate Pallada) provide relatively more issues of authors individual lexical compatibility for these words, than texts created by others; in addition a full list of syntagmatically active words for Goncharovs texts is represented in this article. Context analysis is conducted to show, how semantic connections between words in contexts reflect conceptual characteristics of Goncharovs idiostyle. Comments on the individual use of words zhizn (life) and zhit (live) by other writers A.P. Chekhov, L.N. Tolstoy, I.S. Turgenev and F.M. Dostoevsky are given. Conclusions are drawn about perspectives of performing comparative statistical analysis of lexical syntagmatics in modern philology

Idiostyle Characteristics of Lexical Compatibility in the 19th-Сentury Prose: Ural Stylometric Project

The article presents the project of the Ural Federal University scientists connected with the formalized study of lexical compatibility in Russian classical prose of the 19th century. The study aims to identify idiostylistic characteristics of individual-author syntagmatic. A lexical bigram – a pair of words extracted from one phrase context – is accepted as a unit of compatibility. With the help of their corpus of classical prose (works by Leo N. Tolstoy, Fyodor M. Dostoyevsky, Anton P. Chekhov, Ivan S. Turgenev and Ivan A. Goncharov), the project participants carried out a comparative statistical analysis of lexical bigrams typical for the works of each author and not found in the texts of other writers. A prerequisite for the selection of material is that one of the words constituting a bigram is often used by all authors. Thus, based on the lexical fund common to all authors, the idiostylistical peculiarities of lexical compatibility are revealed. The results of the study are presented on the example of the author’s use of adverbs in the works of Fyodor M. Dostoevsky and comparison of syntagmatic characteristics of these adverbs with their textual embodiment in the works of other four authors. Conclusions are made about stylometric perspectives of formalized research of syntagmatic for idiostylistics and author’s lexicography

Meaning composition in minimal phrasal contexts: distinct ERP effects of intensionality and denotation

ABSTRACT A central question in neurolinguistics is how the brain computes the meaning of complex expressions from the meanings of the parts. We investigate adjective–noun composition using EEG, focusing on the effects of the intensional and denotational semantics of the modifying adjective. We used NPs from 4 semantic conditions in Bokmål Norwegian: privative modal (e.g. “fake president”), privative temporal (“former president”), non-privative modal (“real president”), and non-privative temporal (“current president”). In 2 non-semantic conditions, the adjective was replaced by either a non-word or a pseudo-word. The composition contrast (semantic vs non-semantic trials) revealed a larger P600 component after the noun in the semantic trials. The effects of intensionality (modal vs temporal adjective) were found in the N400 time frame, while the effects of denotation (privative vs non-privative adjective) were found in a post-N400 window. We discuss some implications of these results for neurocognitive theories of compositional language processing.

Alternating Language Modeling for Cross-Lingual Pre-Training

Language model pre-training has achieved success in many natural language processing tasks. Existing methods for cross-lingual pre-training adopt Translation Language Model to predict masked words with the concatenation of the source sentence and its target equivalent. In this work, we introduce a novel cross-lingual pre-training method, called Alternating Language Modeling (ALM). It code-switches sentences of different languages rather than simple concatenation, hoping to capture the rich cross-lingual context of words and phrases. More specifically, we randomly substitute source phrases with target translations to create code-switched sentences. Then, we use these code-switched data to train ALM model to learn to predict words of different languages. We evaluate our pre-training ALM on the downstream tasks of machine translation and cross-lingual classification. Experiments show that ALM can outperform the previous pre-training methods on three benchmarks.1

Embedding (im)plausible clauses in propositional attitude contexts: Modulatory effects on the N400 and late components

Abstract How do comprehenders track dependencies between the plausibility of embedded clauses and of the sentences in which they occur? We investigated processing of Norwegian propositional attitude sentences with plausible or implausible complement clauses (‘Magnus {knows/believes/dreams/doubts/imagines} that mosquitos live off {blood/vodka}’). Using ERPs, we tested the hypothesis that the amplitude of the N400 component is sensitive to the plausibility of the attitude sentence as a whole, as opposed to that of the complement clause. If the hypothesis is correct, the N400 should be larger for implausible clauses (vodka > blood) under know and believe, it should be canceled (vodka ~ blood) under dream, and it should be reversed (vodka blood), except for imagine (‘innbille’ in Norwegian has a counterfactual sense), where the effect was suppressed, but not reversed. Moreover, we observed modulations of late ERP components for implausible clauses (vodka > blood) under doubt and imagine, i.e., when the plausibility of the attitude sentence requires an implausible complement clause. We propose that (a) the N400, in general, reflects processing of semantic relations in phrasal and clausal contexts, and it is not necessarily sensitive to sentence plausibility, and (b) later components index integration of information from embedded clauses into a sentence model.

CONVOLUTIONAL NEURAL NETWORK MULTI-EMOTION CLASSIFIERS

The natural languages are universal and flexible but cannot exist without ambiguity. Having more than one attitude and meaning in the same phrase context is the main cause for word or phrase ambiguity. Most previous work on emotion analysis has only coverage single-label classification and neglect the presence of multiple emotion labels in one instance. This paper presents multi emotion classification in Twitter based on Convolutional Neural Networks (CNN). The applied features are emotion lexicons, word embeddings, and frequency distribution. The proposed networks performance is evaluated to state-of-the-art classification algorithms, achieving hamming score ranges from 0.46 to 0.52 on the challenging SemEval2018 Task E-c.