Language Comprehension Research Articles

Language impairment in sporadic and familial (type 8) amyotrophic lateral sclerosis: A comparative study.

Language is frequently affected in patients with sporadic amyotrophic lateral sclerosis (sALS), with reduced performance in naming, syntactic comprehension, grammatical expression, and orthographic processing. However, the language profile of patients with familial type 8 ALS (ALS8), linked to p.P56S VAPB mutation, remains unclear. We investigated language in patients with ALS8 by examining their auditory comprehension and verbal production. We included three groups of participants: (1) patients with sALS (n = 20), (2) patients with familial ALS8 (n = 22), and (3) healthy controls (n = 21). The groups were matched for age, sex, and education level. All participants underwent a comprehensive language battery, including the Boston Diagnostic Aphasia Examination, the reduced Token test, letter fluency, categorical fluency (animals), word definition from the Cambridge Semantic Memory Research Battery, and a narrative discourse analysis. Participants also were evaluated using Addenbrooke's Cognitive Exam-Revised Version, the Hospital Anxiety and Depression Scale, and the ALS Functional Rating Scale-Revised. Compared to controls, sALS and ALS8 patients had impaired performance on oral (syntactic and phonological processing) comprehension and inappropriate discourse cohesion. sALS and ALS8 did not differ in any language measure. There was no correlation between language scores and functional and psychiatric scales. ALS8 patients exhibit language deficits that are independent of motor features. These findings are consistent with the current evidence suggesting that ALS8 has prominent non-motor features.

Fast Recurrent Neural Network with Bi-LSTM for Handwritten Tamil Text Segmentation in NLP

Tamil text segmentation is a long-standing test in language comprehension that entails separating a record into adjacent pieces based on its semantic design. Each segment is important in its own way. The segments are organised according to the purpose of the content examination as text groups, sentences, phrases, words, characters or any other data unit. That process has been portioned using rapid tangled neural organisation in this research, which presents content segmentation methods based on deep learning in natural language processing (NLP). This study proposes a bidirectional long short-term memory (Bi-LSTM) neural network prototype in which fast recurrent neural networks (FRNNs) are used to learn Tamil text group embedding and phrases are fragmented using text-oriented data. As a result, this prototype is capable of handling variable measured setting data and gives a vast new dataset for naturally segmenting text in Tamil. In addition, we develop a segmentation prototype and show how well it sums up to unnoticeable regular content using this dataset as a base. With Bi-LSTM, the segmentation precision of FRNN is superior to that of other segmentation approaches; however, it is still inferior to that of certain other techniques. Every content is scaled to the required size in the proposed framework, which is immediately accessible for the preparation. This means, each word in a scaled Tamil text is employed to prepare neural organisation as fragmented content. The results reveal that the proposed framework produces high rates of segmentation for manually authored material that are nearly equivalent to segmentation-based plans.

A Systematic Review of Using Deep Learning in Aphasia: Challenges and Future Directions

In this systematic literature review, the intersection of deep learning applications within the aphasia domain is meticulously explored, acknowledging the condition’s complex nature and the nuanced challenges it presents for language comprehension and expression. By harnessing data from primary databases and employing advanced query methodologies, this study synthesizes findings from 28 relevant documents, unveiling a landscape marked by significant advancements and persistent challenges. Through a methodological lens grounded in the PRISMA framework (Version 2020) and Machine Learning-driven tools like VosViewer (Version 1.6.20) and Litmaps (Free Version), the research delineates the high variability in speech patterns, the intricacies of speech recognition, and the hurdles posed by limited and diverse datasets as core obstacles. Innovative solutions such as specialized deep learning models, data augmentation strategies, and the pivotal role of interdisciplinary collaboration in dataset annotation emerge as vital contributions to this field. The analysis culminates in identifying theoretical and practical pathways for surmounting these barriers, highlighting the potential of deep learning technologies to revolutionize aphasia assessment and treatment. This review not only consolidates current knowledge but also charts a course for future research, emphasizing the need for comprehensive datasets, model optimization, and integration into clinical workflows to enhance patient care. Ultimately, this work underscores the transformative power of deep learning in advancing aphasia diagnosis, treatment, and support, heralding a new era of innovation and interdisciplinary collaboration in addressing this challenging disorder.

The Operational Laws of Symmetric Triangular Z-Numbers

To model fuzzy numbers with the confidence degree and better account for information uncertainty, Zadeh came up with the notion of Z-numbers, which can effectively combine the objective information of things with subjective human interpretation of perceptive information, thereby improving the human comprehension of natural language. Although many numbers are in fact Z-numbers, their higher computational complexity often prevents their recognition as such. In order to reduce computational complexity, this paper reviews the development and research direction of Z-numbers and deduces the operational rules for symmetric triangular Z-numbers. We first transform them into classical fuzzy numbers. Using linear programming, the extension principle of Zadeh, the convolution formula, and fuzzy number algorithms, we determine the operational rules for the basic operations of symmetric triangular Z-numbers, which are number-multiplication, addition, subtraction, multiplication, power, and division. Our operational rules reduce the complexity of calculation, improve computational efficiency, and effectively reduce the information difference while being applicable to other complex operations. This paper innovatively combines Z-numbers with classical fuzzy numbers in Z-number operations, and as such represents a continuation and innovation of the research on the operational laws of Z-numbers.

A Paradigm for the missing middle

ABSTRACT This commentary highlights what I see as the most important of Walter Kintsch’s many contributions to cognitive psychology and especially text comprehension. His work filled the great void between the top and the bottom in research on comprehension. The state of the field at the time was (a) strong research foundation on word reading, (b) detail-focused research on syntactic processes by a vibrant sentence processing research community, and (c) demonstration research on the importance of higher-level top down influences. The void between (b) and (c) meant there was no possibility of a comprehension science that was both rigorous, like (a) and (b), and reflective of the role of outside-the-text knowledge, like (c). Beyond the specific empirical contributions of Kintsch’s work is that he showed that it was possible to create a paradigm for the missing middle, a characterization of how word-driven and knowledge-driven processes yield a coherent meaning-based understanding of a text a few pieces at a time. This allowed the flourishing of work on the incremental processes that result in a reader’s (often) coherent representation of text meaning.

Negation and social avoidance in language recruits the right inferior frontal gyrus: a tDCS study

IntroductionIn the process of comprehension, linguistic negation induces inhibition of negated scenarios. Numerous studies have highlighted the role of the right Inferior Frontal Gyrus (rIFG) - a key component of the inhibitory network - in negation processing. Social avoidance can be linguistically portrayed using attitudinal verbs such as “exclude” vs. “include”, which inherently carry negative connotations. Consequently, we hypothesize that the interplay between explicit negation and the implicit negativity of avoidance verbs can be modulated via transcranial direct current stimulation (tDCS) targeting the rIFG.MethodsIn our study, sixty-four participants read approach/avoidance sentences, which were either affirmative or negative, such as “Anne included (did not include) meat in her diet” vs. “Anne excluded (did not exclude) meat in her diet”. This reading task followed a 20-minute tDCS session. The sentences were sequentially displayed, and at 1500 ms post-sentence, a verb was shown – either the one previously mentioned or its semantic alternative counterpart (e.g., included vs. excluded).ResultsFindings revealed that anodal stimulation intensifies the inhibitory impact of negation during sentence comprehension. Under anodal conditions, negative sentences led to extended reading times for the mentioned verbs compared to their affirmative counterparts, suggesting an increased inhibitory effect on the verb. Furthermore, in avoidance sentences, anodal stimulation resulted in reduced reading times for alternative verbs (e.g. “included”) in negative sentences compared to alternative verbs (e.g. “excluded”) in negated approach sentences.DiscussionAs “avoidance” is semantically equivalent to “non-approach”, the inhibitory effect of negation is primarily applied to the implicit negation: NOT EXCLUDED = NOT→NOT (INCLUDED), which consequently activates the representation of the alternative verb making it more available. We further discuss these findings in light of the rIFG’s pivotal role in processing attitudinal verbs and linguistic negation. This discussion is framed within the overarching context of the two-step model of negation processing, highlighting its significance in the realm of social communication.

Overcoming Language Barriers in Contracts – A South African Perspective

Language forms the basis of written contracts, but the use of language may also function as a barrier to contracting parties, particularly when the parties are not proficient in the commercial language of choice, such as English in the case of South Africa. The plain language movement and specifically legislative interventions have placed significant pressure on lawmakers to reform the use of traditional legal English, and consequently, traditional drafting styles. However, many contracts continue to exhibit convoluted language, legalese and poor visual appeal, which ultimately functions as a language barrier for many people. This article examines the various language barriers that exist in contracts from a South African perspective. It does so by assessing the barriers that exist under first, the common law (or the so-called default rules), second, the use of standard contracts, and third, the resistance to the use of plain language as well as the limited application of existing plain language legislation in certain types of contractual engagements. The author proposes dismantling the language barriers by adopting both textual and visual communication devices in order to achieve clear and comprehensible language in all types of contracts. Furthermore, it is suggested that such communication devices should not necessarily be limited to consumer contracts that are legislatively required to comply with plain language requirements. It is only by dismantling existing language barriers that social justice within contracts can be achieved in a society with diverse language proficiencies, such as South Africa. Therein, this article offers insights that are relevant not only within the South African context but also for countries that may face similar language barriers characterised by multiple languages and varying language proficiencies within their populations.

The role of prediction error in the development of language learning and memory

AbstractPrediction error plays a pivotal role in theories of learning, including theories of language acquisition and use. Researchers have investigated whether and under which conditions children, like adults, use prediction to facilitate language comprehension at different levels of linguistic representation. However, many aspects of the reciprocal relation between prediction error and the development of language learning remain unclear. In this article, we review studies in language development that can inform us about the role of prediction error in updating, learning, and retrieving linguistic information. We argue that the study of individual differences in linguistic and cognitive skills will help the field understand more thoroughly whether, when, and why prediction aids language learning, and whether prediction error necessarily results in language learning and retrieval from memory. We close with a discussion of the needs and challenges for researchers to answer these questions.

Consumer Profiles and Drink Menus Made from Medicinal Plants at the Jamu Cafe in Depok Sleman District, Yogyakarta

The use of medicinal plants as ingredients in making drinks in cafes is increasing along with the number of cafes. Herbal café makes a unique menu using medicinal plants in drink recipes to produce a distinctive taste, color, and aroma. This research aims to identify visitor profiles and drink menus made from medicinal plants and explore the understanding of visitors and cafe owners regarding the benefits of medicinal plants added to drinks. The research data collection technique uses a questionnaire equipped with an interview sheet. The questionnaires and interview sheets used have been tested for language comprehension and validity. The research was conducted at 272 cafes in Depok District, Sleman Regency, Special Region of Yogyakarta. The sample was determined using purposive sampling, data was collected after obtaining ethical clearance approval from the Health Research Ethics Committee Team. Data was obtained through filling out surveys by visitors and cafe owners, complemented by interviews with cafe owners. Data was collected three times: August, September, and October 2023. Data analysis was carried out descriptively and qualitatively. Most herbal cafe visitors (70%) are aged between 21–30 years with the majority of professions (44%) being students. The source of information about herbal cafe menus was mostly obtained (56%) from friends or family, and the frequency of visits to cafes was mostly (82%) between 1–5 times per month. More than 98% of visitors stated the benefits of medicinal plants in the drink menu, namely as a refresher or body warmer. There are 14 types of medicinal plants used as ingredients in the herbal cafe's drink menu, with a total monthly requirement for all medicinal plants of 545.1 kilograms; ginger ranks among the highest requirements. Recipe information for the menu was obtained from the family, the Ministry of Health Republic Indonesia website, and the herbal cafe owner made the recipe independently.

Exploring the Interplay Between Language Comprehension and Cortical Tracking: The Bilingual Test Case

Abstract Cortical tracking, the synchronization of brain activity to linguistic rhythms is a well-established phenomenon. However, its nature has been heavily contested: Is it purely epiphenomenal or does it play a fundamental role in speech comprehension? Previous research has used intelligibility manipulations to examine this topic. Here, we instead varied listeners’ language comprehension skills while keeping the auditory stimulus constant. To do so, we tested 22 native English speakers and 22 Spanish/Catalan bilinguals learning English as a second language (SL) in an EEG cortical entrainment experiment and correlated the responses with the magnitude of the N400 component of a semantic comprehension task. As expected, native listeners effectively tracked sentential, phrasal, and syllabic linguistic structures. In contrast, SL listeners exhibited limitations in tracking sentential structures but successfully tracked phrasal and syllabic rhythms. Importantly, the amplitude of the neural entrainment correlated with the amplitude of the detection of semantic incongruities in SLs, showing a direct connection between tracking and the ability to understand speech. Together, these findings shed light on the interplay between language comprehension and cortical tracking, to identify neural entrainment as a fundamental principle for speech comprehension.

A Literature Review of Language Characteristics in Patients with Vascular Dementia

Vascular dementia may present with language disorders due to damage to frontal subcortical circuits. This study aimed to review recent studies of language abilities in patients with vascular dementia. Sixty-nine studies were classified according to language modalities (spontaneous speech, auditory comprehension, repetition and naming). First, spontaneous speech was impaired in the ability to describe pictures, objects and in the ability to convey information in discourse. Second, the auditory comprehension was impaired in word comprehension, sentence comprehension, paragraph comprehension, and speech act comprehension tasks. Third, repetition was preserved in word-level tasks but impaired at the sentence level. Fourth, the naming performance was impaired in a generative naming task (phonemic fluency) rather than in a confrontational naming task. Therefore, when summarizing the results between patient groups, in spontaneous speech, to convey information through highly informative utterances was relatively good in vascular dementia (VaD), but the number of utterances was lower than dementia of Alzheimer’s type (DAT). In auditory comprehension, VaD’s performance was good in the task of word comprehension and speech act comprehension tasks. It is organized as in repetition, VaD’s performance was relatively good in the sentence-level task, and in naming, VaD’s performance was reported to be better than DAT in the oppositional naming and generative naming semantic category tasks. In the generative naming phoneme category, opposite result was reported. Further studies on the language abilities of patients with vascular dementia needs to consider factors such as subtype and language modality. Future studies should be evenly distributed across all language domains.

Developmental Profile in Children Aged 3–6 Years: Down Syndrome vs. Autism Spectrum Disorder

This research aims to compare the developmental profiles of children with autism spectrum disorder (ASD) and children with Down Syndrome (DS) between the ages of 3 and 6 years. The study examines whether these developmental disorders share common developmental milestones or exhibit distinctive characteristics. A total of 43 children, 23 with DS and 20 with ASD, participated in the study. Cognitive and language skills were assessed using standardized tools, including the Battelle Developmental Inventory, Reynell Developmental Language Scales III, and NEPSY-II battery. The results indicated that children with ASD outperformed children with DS in the areas of fine motor skills, gross motor skills, and communication. Additionally, children with ASD demonstrated higher scores in language comprehension and expressive language, compared to children with DS. Significant correlations were found between motor skills and communication abilities. Neuropsychological evaluations revealed significant differences between the two groups in various tasks, such as the comprehension of instructions, body part naming and identification, and recognition of emotions. These findings contribute to our understanding of the similarities and differences between ASD and DS, shedding light on the dissociation between cognition and language and its impact on adaptive functioning in these populations.

Curriculum Approaches in English Language Teaching in Indonesia

This study used library research research methods to investigate curriculum approaches in English language teaching in Indonesia. The purpose of this study is to identify curriculum approaches commonly used in English language teaching in Indonesia and to understand how these approaches shape teaching methods and strategies applied in language classrooms. In this study, the author conducted a comprehensive literature review of relevant literature, including textbooks, research journals, articles, and education policies related to English language teaching in Indonesia. The data collected were analyzed qualitatively to identify curriculum approaches commonly used in the context of English language teaching in Indonesia. The results of this study show that some curriculum approaches commonly used in English teaching in Indonesia include content-based approaches, communicative approaches, task-based approaches, and grammar-based approaches. The selection of this curriculum approach is based on the goals and objectives of the program, as well as the needs and interests of learners. In conclusion, in Indonesia, English teaching is influenced by various curriculum approaches, which shape the methods and strategies applied in language classes. The choice of curriculum approach in English language teaching depends on the goals and objectives of the program, as well as the needs and interests of learners. Different approaches can be used in combination to create a comprehensive and effective language learning experience so that language learners can easily master the language in a formal setting.

Analysis of the Pros and Cons of ChatGPT for College Paper Writing

Chat GPT is a chatbot system that utilizes natural language processing and deep learning technologies to mimic human discussions, potentially reaching or exceeding human intelligence. Recently, Chat GPT has shown significant advancements in various areas, particularly in natural language comprehension, automated question answering, and intelligent customer support, demonstrating promising possibilities. As Chat GPT technology advances and becomes popularity, there are concerns over whether it may bring an end to traditional university essays. This study utilizes a questionnaire-based research methodology to examine the advantages and disadvantages of including ChatGPT in the dissertation writing process for university students. The study seeks to investigate the variables affecting students' inclination to utilize these items, including gender, age, field of study, and prior exposure to comparable products, as well as the potential repercussions on academic integrity.

Psychometric Test for Medical Consultancy System

Abstract: Preliminary investigations delve into the possibility of employing chatbots in psychiatric therapy to aid behavior modification through assessments and chatbot interventions. Nevertheless, these platforms overlook the mental conditions of users, neglecting interviews, continuous surveillance, or ethical factors. We propose that enhancing emotion detection could boost user contentment among individuals seeking mental health assistance. Our suggestion encompasses an interactive psychiatric counseling service employing sophisticated natural language comprehension and multimodal emotion detection. This method permits ongoing and delicate observation of emotional fluctuations. Moreover, an instance-oriented reaction model, integrating moral discernment, facilitates suitable clinical reactions in psychiatric consultations.

Processing wh-filler-gap dependencies.

We present experimental evidence showing that different wh-filler-gap dependencies are processed differently, depending on their syntactic licensors. Our studies compared the active storage profiles for why, how, and who (serving as subject or object of the verb). The results of offline and online experiments revealed that these wh-fillers are stored in memory for different durations, and predictably so based on the hypothesised structural distance between each wh-filler and the licensor which determines its grammatical and interpretive functions. Furthermore, the results showed that once the wh-filler is licenced, it is integrated to the current structure, and no longer engenders additional memory costs. Based on these findings, we argue that the mechanism of online sentence processing may employ both storage and integration components in memory.

IMPLEMENTATION OF ARABIC LEARNING CURRICULUM FOR GRADE VIII AT MTS DARUL ULUM: AN INTERDISCIPLINARY STUDY IN ARABIC EDUCATION

This study is prompted by the pivotal role of the curriculum in shaping Arabic language learning outcomes, necessitating its continuous refinement to align with educational objectives. Employing a qualitative approach with a descriptive research design, the research delves into the Arabic language curriculum for eighth-grade students at MTs Darul Ulum Beraim. The primary objective is to evaluate the curriculum's components, including objectives, content, instructional methods, and assessment strategies. Findings underscore a gap in the curriculum's focus on fostering interactive communication skills, both orally and in writing, with current materials primarily centered on vocabulary and texts related to personal experiences. Consequently, there is a pressing need to revamp the curriculum to prioritize comprehensive language proficiency development, facilitating effective communication in various contexts. This study advocates for curriculum enhancements aimed at equipping students with robust linguistic skills vital for their academic and real-world success in Arabic language proficiency

A Blended Teaching Model of College English Based on Deep Learning

Blending traditional face-to-face instruction with online learning components, this model aims to enhance student engagement and improve learning outcomes. This paper introduces a novel blended teaching model for college English courses, integrating Conditional Random Field (CRF) techniques with deep learning frameworks. Blended learning, combining traditional face-to-face instruction with online learning components, has gained traction in higher education for its potential to enhance student engagement and learning outcomes. CRF blended teaching integrates the principles of conditional random fields, a powerful probabilistic graphical model, with traditional teaching methodologies to enhance learning outcomes. Unlike conventional teaching approaches that often rely on linear or static instructional methods, CRF blended teaching embraces a more dynamic and adaptive framework. By leveraging CRF, which models the dependencies between different instructional variables, educators can design personalized learning experiences tailored to individual student needs and learning styles. This approach enables the seamless integration of diverse instructional modalities, including face-to-face instruction, online resources, and interactive learning activities. The proposed model CRF algorithms to effectively capture the sequential dependencies inherent in language learning tasks, such as sentence parsing and part-of-speech tagging. By integrating deep learning architectures, including recurrent neural networks (RNNs) and transformers, model with large-scale linguistic corpora to improve accuracy and generalization. The model achieves a 15% increase in students' English proficiency scores and a 25% improvement in comprehension compared to traditional teaching methods, underscoring its effectiveness in enhancing learning outcomes.

Trilingual parallel processing: Do the dominant languages grab all the attention?

Abstract Twenty-five L1 Nepali speaking participants living in Trondheim, Norway who spoke English as L2 and Norwegian as L3 (late adult learners) participated in this study. Participants’ L2 proficiency was established as advanced in LexTALE. We administered language comprehension and production tasks in a trilingual design. In a mouse tracking trilingual parallel activation experiment, participants performed a language comprehension task in which they listened to the spoken word in their L1, L2 and L3 and clicked on the matching target picture. Mouse trajectories of their response pattern were recorded and analyzed. The language production task included a phonological and a semantic verbal fluency task (VFT), which also served as an executive control task. VFT showed their dominance in L1 and L2 compared to L3. This study contributes novel knowledge on trilingual parallel activation and suggests that in the presence of a non-dominant L3, a dominant L1 and a dominant L2 are processed faster than the non-dominant language in phonologically competing conditions.

Design and Application of English-Chinese Bilingual Teaching Model Based on Multimodal Learning

In the globalized landscape of education, the demand for effective bilingual teaching models has become increasingly prominent, particularly in English and Chinese instruction. this study introduces the Bilingual Teaching Random Conditional Field (BTRCF) as a novel approach to designing and implementing an English-Chinese Bilingual Teaching Model based on Multimodal Learning. The principles of multimodal learning, which integrates various modes of communication such as visual, auditory, and kinaesthetic, the BTRCF model aims to provide students with a comprehensive and immersive language learning experience. The BTRCF model capitalizes on the complementary strengths of both English and Chinese languages, aiming to cultivate bilingual proficiency while fostering cross-cultural understanding among students. By incorporating elements from each language and leveraging multimodal learning strategies, the BTRCF model provides students with a comprehensive language learning experience that extends beyond mere linguistic proficiency to encompass cultural appreciation and intercultural competence. By capitalizing on the complementary strengths of both languages, this model seeks to foster bilingual proficiency while promoting cross-cultural understanding among students. with the BTRCF model have shown promising results, with an average increase of 25% in students' bilingual proficiency scores compared to traditional teaching methods. Additionally, qualitative assessments reveal high levels of student engagement and satisfaction with the multimodal learning approach employed by the BTRCF model, indicating its potential to revolutionize bilingual education practices.