Word Level Research Articles

PHONOLOGICAL ANALYSIS OF LANGUAGE PRODUCTION IN PRESCHOOL CHILDREN

The paper presents an analysis of the phonological features of preschool children. The article aims to find patterns of typical and atypical errors. A method was created to conduct the study, which includes three levels of research - at the level of words, sentence repetition, and generating one's speech by picture (spontaneous speech). The results show that children's most common phonological errors are as follows: sound substitution, elision of sound, metathesis of sound, elision of syllable, and deletion of consonants clustered in a syllable. The data obtained from the noun generation task was informative enough about the phonological development of the children being studied. The repeated speech task was accessible for the children and of little value in analyzing the phonological processes. The sentence generation task provides sufficient information about sentence structure, prosody, rate, and force of speech. The test serves a diagnostic and therapeutic purpose. The diagnostic analysis is clear and informative enough to create a therapeutic program based on the examination results. Subsequently, it could be applied for re-testing to measure the progress in the child's output. In addition, the average time children take to administer the whole test is less than 18 minutes, which is an additional positive aspect of the test. The ultimate goal is to standardize this test to assist clinicians in establishing norms by examining Bulgarian-speaking children and assessing their phonological development.

Academic language use in middle school informational writing.

Learning to write the complex academic language (AL) associated with a discipline (like science) is a critical task in education, with middle school being a key developmental period. However, we need more research to guide how we assess students' learning to write AL, especially if we want to create assessment that guides more effective instruction. We evaluated middle school students' informational writing for six different measures of AL to determine which ones were most strongly related to writing quality and were most indicative of the unique features of informational writing. We also examined which metrics were sensitive to growth across middle school. Our sample consists of informational compositions from 285 students in Grade 5 (n = 175) and Grade 8 (n = 110) in a Midwestern state in the United States. Path modelling was used to determine the degree to which the AL metrics are associated with writing quality and narrativity in each grade. Overall, the six measures of AL explained 70% of the variance in students' writing quality. We found that a new measure, number of long words, outperformed other more established measures at the word level and should be used in assessment of informational writing quality. We also found that automated scores at the sentence level better detected development across middle school grade levels than typical rubrics of writing quality. Results provide promising avenues for the assessment of malleable aspects of AL in middle school informational writing.

Research Trends in the Evaluation and Treatment of Speech Disorders Using Automatic Speech Recognition (ASR)

Purpose: The purpose of this study is to examine recent research trends regarding automatic speech recognition (ASR), which is used in the evaluation and intervention of speech disorders.Methods: Through a search engine, articles published in domestic journals were searched. A total of 27 papers were selected from the searched documents and analyzed according to the year, research subject, speech task, and ASR system.Results: The years with the most research was done in 2019~2021. The subjects who most frequently underwent speech evaluation and treatment using ASR system were those with dysarthria. The speech production tasks used to utilize ASR were at the word and sentence level, and commercialized and non-commercialized ASR systems were used similarly.Conclusion: These results might be used for the fundamental data to establish the most suitable evaluation methods and intervention plans for patients with speech disorders in clinical and research fields.

의사소통적 발음 교육을 위한 한국어 교재 분석 연구

Objectives The purpose of this paper is to analyze Korean textbooks for communicative pronunciation education. Methods Three types of textbooks developed by university-affiliated language education institutes were selected as analysis targets. As analysis tools, items that were synthesized and reconstructed from the textbook analysis frameworks of Seo (2001) and Lee (2001) were used. Results The result shows that the scope of teaching items was expanded, and it was necessary to secure areas equivalent to vocabulary and grammar, select teaching items for continuous and repetitive learning, and provide detailed grading. In addition, the educational effectiveness of the explicitness or implicitness of linguistic rule explanations had to be examined, and audiovisual materials should be abundantly utilized. The practice activities were planned to involve step-by-step practice from the word and sentence level to the discourse level, but the instructions were not clear, and even if there were directions, practice method was monotonous. For communicative pronunciation education, instructions and guidelines had to be specified and a variety of interactive and meaningful exercises had to be included. As for learning strategies, only simple repetition, memorization strategies, and strategies using visual images were induced. Effective pronunciation learning strategies should be found and learning strategies had to be developed in a variety of ways. Conclusions Considering practical application, a plan to revitalize pronunciation education was proposed while maintaining the current textbook. Improvement measures were discussed focusing on the practice stage. Integrated practice with other micro and macro skills and clear practice method instructions were emphasized. Practice and use were claimed at the word, sentence, and discourse levels in the order of presentation-controlled practice-meaningful practice-use. Interactive activities such as pair or group activities were considered.

Constrained Emotional Sentence Production in Parkinson's Disease.

Deficits in the processing and production of emotional cues are well documented in the Parkinson's disease (PD) literature; however, few have ventured to explore how impairments may impact emotional language use in this population, particularly beyond the word level. Emotional language is an important multidimensional manner of communicating one's wants and needs; thus, the current study sought to explore how various aspects of language production may be impacted by the emotionality of a stimulus. Eighteen persons with PD and 22 healthy adults completed a constrained emotional sentence production task in which the affective target word was either a noun or a verb. Output was analyzed for fluency, grammaticality, completeness, and response initiation times. Cognitive (i.e., working memory [WM], inhibition, and switching) and mood (i.e., depression and apathy) measures were examined as factors influencing performance. Individuals with PD produced fewer fluent responses than healthy controls. Furthermore, they had fewer grammatical responses in their production of negative sentences and exhibited reduced information completeness when producing sentences containing positive stimuli. Group differences could not be wholly attributed to individual differences in WM or apathy. Our results support those of others that document language production deficits in individuals with PD above and beyond those impairments that can be explained by the select cognitive abilities explored here. Moreover, the emotionality of the topic may impact various aspects of communicative competence in persons with PD. For instance, disease processes associated with degeneration of neural substrates important for processing negative stimuli may also impact the grammaticality of productions containing negatively valenced content. Thus, it is important to consider how individuals in this population communicate during emotional circumstances. https://doi.org/10.23641/asha.27289413.

Listening comprehension in a home language: a case of Russian in Germany.

Listening comprehension is central to language learning, yet it remains the least understood and least researched skill. This statement is still relevant today, as there is insufficient research to explore listening comprehension from the perspective of family-related multilingualism and to consider the complete linguistic repertoire of multilingual speakers. Moreover, with regard to home language, listening comprehension is assumed to be a more developed language competence than reading or writing. Based on the mentioned research, the aim of the present study is to investigate listening comprehension and its influencing factors specifically in German-Russian simultaneous bilinguals aged 13-19 (n = 99) by considering the home- and majority language. The study uses quantitative data collection methods such as linguistic tests in Russian and German for the elicitation in different levels of listening and questionnaires for strategy use and background. The research questions are as follows: What does the language proficiency and input in Russian look like? (1) Regarding listening comprehension in Russian as a home language, are there differences between the speakers within comprehension on different levels, e.g., is sound decoding easier than sentence parsing? (2) If there are differences in Russian as a home language, which linguistic and background variables can correlate with the performance of listening comprehension on its different levels? Concerning the first research question, the results show relevant differences between four different levels of listening comprehension (phoneme, word, sentence, and text level), which strengthened the assumed complexity of listening comprehension in the home language. In addition, the results show different connections between the listening comprehension competence and the input from different family members, as well as exposure to film and television in the home and majority language.

SỬ DỤNG GOOGLE DOCS VÀ MERCI APP TRONG LỚP HỌC VIẾT TIẾNG PHÁP

This study compares the effectiveness of two automated feedback tools, Google Documents, which will be further addressed as Google Docs, and Merci App, in improving writing ability in French as a foreign language. Forty second-year students used these two reviewer tools to correct their B2-level texts. The data includes 80 student drafts edited on two tools and a survey questionnaire after using these two applications. The results show that both tools help students correct many errors at the sentence, word, and fragment levels but cannot correct errors at the inter-sentence, idea, and coherence levels. Google Docs detects more grammatical errors than Merci App, but Merci App is superior when it comes to finding errors in spelling, vocabulary, expression, and punctuation. Students use the application's error correction suggestions to correct their papers at a very high rate, 92.6% with Google Docs and 81.7% with Merci App. The number of students who prefer Google Docs is also higher than the number of students who prefer Merci App. The study proposes to use both tools to correct students' writing errors and to help students become familiar with error explanations in Merci App to help them systematize language knowledge and develop auto-learning capacity.

Hearing, speech, and language outcomes in school-aged children after cleft palate repair.

Following primary cleft palate repair, individuals face a heightened risk of hearing problems, particularly conductive hearing loss, compensatory articulation disorders (CADs), resonance disorders, delayed speech and language development, and voice disorders. This study aimed to investigate the prevalence and impact of these challenges in children with cleft palate with or without cleft lip (CP± L). This cross-sectional study included 38 children with CP± L aged 5 to 13 years. A comprehensive evaluation involved audiological assessments (audiograms, tympanograms) by an audiologist and speech-language pathology assessments (Thai Speech Parameters for Patients with Cleft Palate, Articulation Screening Test) by speech-language pathologists. The prevalence of hearing loss affected 27.63% of participants (21 out of 76 ears) and majority of cases involved conductive hearing loss. Velar substitution was the most common CAD, followed by nasalized voiced pressure consonants, phoneme-specific nasal air emission, and pharyngeal substitution. A moderate correlation was found between these CAD patterns and hypernasality at the word, sentence, and screening levels (r= 0.44, p< 0.01; r= 0.43, p< 0.01; and r= 0.40, p= 0.01). For summary, the most common type of hearing loss was conductive hearing loss. The predominant CAD pattern was velar substitution. The protocol could be designed to enhance early improvement in hearing and articulation, thereby supporting academic achievement and long-term quality of life.

Def2Vec: you shall know a word by its definition

AbstractDef2Vec introduces a new perspective on building words embeddings by using dictionary definitions. By leveraging term-document matrices derived from dictionary definitions and employing Latent Semantic Analysis (LSA), our method, Def2Vec, yields embeddings characterized by robust performance and adaptability. Through comprehensive evaluations encompassing token classification, sequence classification and semantic similarity, we show empirically how Def2Vec consistently demonstrates competitiveness with established models like Word2Vec, GloVe, and FastText. Notably, our model’s utilization of all the matrices resulting from LSA factorisation facilitates efficient prediction of embeddings for out-of-vocabulary words, given their definition. By effectively integrating the benefits of dictionary definitions with LSA-based embeddings, Def2Vec builds informative semantic representations, all while minimizing data requirements. In this paper, we run different experiment to assess the quality of our embedding model at word level and at sequence level. Our findings contribute to the ongoing evolution of word embedding methodologies by incorporating structured lexical information and enabling efficient embedding prediction.

Analyzing Asymmetric Prosody in Salim's Poetry: A Critical Examination of Words, Phrases, Poetic Lines and Punctuations

In this research, titled "Analyzing Asymmetric Prosody in Salim's Poetry: A Critical Examination of words, phrases, poetic lines and punctuations," we conduct a comprehensive and practical analysis to identify errors and asymmetric rhythmic prosody within Salim's poetry, focusing on the edition we have diligently worked on. Our study aims to explore potential solutions in accordance with established prosody criteria. Salim's body of work encompasses several books of poetry, with our research specifically delving into the most recent edition published in 2015 in Sulaimani by Mullah Abdulkarim Mudaris, Fatih Abdulkarim, and Mohammed Mullah Karim. We selected this edition due to its freshness and its incorporation of improvements from previous editions, making it a widely embraced reference among both writers and readers of Salim's poetry. Our research comprises four primary themes. Firstly, we analyze disruptions at the level of words and phrases. Secondly, we investigate instances of rhythmic disruptions resulting at the level of poetic hemistich. Thirdly, we explore disruptions caused at the level of poetic lines. Lastly, we analyze disruptions at the level of punctuations. In conclusion, our study offers valuable insights into the content of Salim's poetry by shedding light on its prosodic nuances and providing potential remedies for asymmetries.

The Effects of Morphological Instruction on Literacy Outcomes for Children in English-Speaking Countries: A Systematic Review and Meta-Analysis

In this pre-registered meta-analysis, we investigated the effectiveness of morphology instruction on literacy outcomes for primary school children in English-speaking countries. We were interested in overall reading and spelling outcomes, but we also looked separately at results for trained and untrained words in order to determine whether there was evidence of transfer to untrained words. Further, we were interested in whether results transferred beyond the word level to reading comprehension outcomes. Our screening process revealed 28 eligible studies, which contributed 177 effect sizes to the analyses. Robust variance estimation methods were used to account for dependence between effect sizes. Overall, effect sizes on reading and spelling outcomes were small to moderate. Effect sizes were larger for trained words than untrained words. There was evidence of transfer to untrained words for spelling outcomes, but not for reading outcomes. There was also no clear evidence of effects on reading comprehension outcomes. In general, the evidence was characterised by large amounts of heterogeneity and imprecision, which was reflective of the wide variety within and between studies in terms of intervention content, outcome measures, intervention dosage and type of control group. We discuss the limitations of the current literature and make recommendations for future research and practice in the field of morphology instruction. (207 words – max 250).

Personalized multi-head self-attention network for news recommendation

With the rapid explosion of online news and user population, personalized news recommender systems have proved to be efficient ways of alleviating information overload problems by suggesting information which attracts users in line with their tastes. Exploring relationships among words and news is critical to structurally model users’ latent tastes including interested domains, while selecting informative words and news can directly reflect users’ interests. Most of the current studies do not provide an effective framework that combines distilling users’ interested latent spaces and explicit points systematically. Moreover, introducing more advanced techniques to merely chase accuracy has become a universal phenomenon. In this study, we design a Personalized Multi-Head Self-Attention Network (PMSN) for news recommendation, which combines multi-head self-attention network with personalized attention mechanism from both word and news levels. Multi-head self-attention mechanism is used to model interactions among words and news, exploring latent interests. Personalized attention mechanism is applied by embedding users’ IDs to highlight informative words and news, which can enhance the interpretability of personalization. Comprehensive experiments conducted using two real-world datasets demonstrate that PMSN efficiently outperforms state-of-the-art methods in terms of recommendation accuracy, without complicated structure design and exhausted even external resources consumption. Furthermore, visualized case study validates that attention mechanism indeed increases the interpretability.

Research on 3D geographic entity recognition method based on the double matching degree

Abstract In the process of real-view 3D construction, the description of the same geospatial object by multiple departments is not the same, and how to link the city’s multi-source datasets to the same entity and construct the mapping relationship between multi-source data has become the current difficulty of multi-source data convergence. A double-matching degree entity recognition method was proposed in this paper for the problem of unified geographic entities in data convergence. Firstly, the address information is extracted from the original address data according to the address elements, and the hierarchical address tree is established by using the organization of a dictionary tree for hierarchical matching. The BERT model and twin neural network are introduced to divide the address information on the remaining paths at the byte and word level to calculate the similarity of address information. Then, the similarity of entity names is calculated by the method based on editing distance, and by combining the string-based method and the neural network-based method with each other, the hierarchical step-by-step matching is performed to narrow the matching space, determine the matching entities, and establish the entity links. Experiments on the self-built dataset show that this method has performed better in entity recognition compared to other methods.

Determinants of Multilevel Discourse Outcomes in Anomia Treatment for Aphasia.

Individuals with aphasia identify discourse-level communication (i.e., language in use) as a high priority for treatment. The central premise of most aphasia treatments is that restoring language at the phoneme, word, and/or sentence level will generalize to discourse. However, treatment-related changes in discourse-level communication are modest, are poorly understood, and vary greatly among individuals with aphasia. In response, this study consisted of a multilevel discourse analysis of archival, monologic discourse outcomes across two high-intensity Semantic Feature Analysis (SFA) clinical trials. Aim 1 evaluated changes in theoretically motivated discourse outcomes representing lexical-semantic processing, lexical diversity, grammatical complexity, and discourse informativeness. Aim 2 explored the potential moderating role of nonlanguage cognitive factors (semantic memory, divided attention, and executive function) on discourse outcomes. This study was a retrospective analysis of archival monologic discourse outcomes after intensive SFA for n = 60 (Aim 1) and a subset n = 44 (Aim 2). Outcome measures included lexical-semantic processing (% semantic errors), lexical diversity (moving average type-token ratio), grammatical complexity (mean utterance length), and discourse informativeness (% correct information units). Bayesian generalized mixed-effects models were used to examine changes across four study time points: enrollment, entry, exit, and 1-month follow-up. The present study found no evidence for meaningful or statistically reliable improvements in monologue discourse performance after SFA when measured using standard, general-topic discourse stimuli. There was weak and inconsistent evidence that nonlanguage cognitive factors may play a role in moderating treatment response. These findings indicate a clear need to pair theoretically informed treatments designed to facilitate generalization to discourse with intentional measurement paradigms designed to capture it. Furthermore, there is a clear need to examine how established treatments, restorative or compensatory, can better facilitate generalization to discourse-level communication. These priorities are critical for meaningfully improving everyday communication and reducing the profound communication and psychosocial consequences of aphasia. https://doi.org/10.23641/asha.26524081.

USE OF TERMINOLOGY AND (META)LINGUISTIC AWARENESS IN GRADE 4 EXPERIENCE FROM A PILOT STUDY

To understand the texts we read, we need language use and linguistic knowledge, as well as metalinguistic awareness related to the text. We examined linguistic and metalinguistic awareness in two areas: at the level of compound words and in relation to words with suffixes. We operated with the following assumptions in our action research: H1: The participants achieve better results in tasks related to affixed words. H2: Those who can justify their answers and reflect on their question answering process using grammatical terms will achieve better results in completing the worksheet. The 15-task test measures metalinguistic knowledge related to compound and suffixed words. The solutions require either implicit or explicit elaboration. Out of the 36 utterances in the "interpretative" text, grammatical metalanguage-related expressions were used by the informants in 13 cases. Through the use of quantitative content analysis, the study could contribute to the development of native language methodology and grammar teaching in lower primary education.

Unveiling the hidden patterns: A novel semantic deep learning approach to fake news detection on social media

The rise of social media as a source of news consumption has led to the spread of fake news, posing serious consequences for both individuals and society. The detection and prevention of fake news are essential, and previous research has shown that incorporating news content along with its associated headlines and user comments can improve detection performance. However, the semantic relationships between these elements have not been fully explored. This paper proposes a novel approach that models the relationships between news bodies and associated headlines/user comments using deep learning techniques, such as fine-tuned Bidirectional Encoder Representations from Transformers (BERT) and cross-level cross-modality attention sub-networks. In our proposed model, we utilize two different configurations of BERT: pool-based representation, which provides a representation of the entire document, and sequence representation, which represents each token within the document (i.e., at the word and text levels). The approach also encodes user-posting behavioural features and fuses the output of these components to detect fake news using a classification layer. Our experiments on benchmark datasets demonstrate the superiority of the proposed method over existing state-of-the-art (SOTA) approaches, highlighting the importance of utilizing semantic relationships for improved fake news detection (FND). These findings have significant implications for combating the spread of fake news and protecting society from its negative effects.

Lip reading using deep learning in Turkish language

&lt;p&gt;Computer vision is one of the most important areas of artificial intelligence and lip reading is one of the most important areas of computer vision. Lip-reading, which is more important in noisy environments or where there is no sound flow, is one of the working areas that can help the hearing-impaired people. There is no dataset in Turkish for lip reading, which there are different datasets at alphabet, word, and sentence level in different languages. The dataset of this study was created by the author and video data were collected from 72 people for 71 words. Audio streams were removed from the collected videos and a dataset was created using only images. Due to the small size of the dataset, the data was replicated with the Camtasia application. After the model of the research was designed and trained, the model was tested on adjectives, nouns, and verbs dataset and success rates of 71.8%, 71.88%, and 79.69% were obtained, respectively.&lt;/p&gt;

Code Mixing Used by Youtuber - Nessie Judge’s Entitled “Pekerjaan-Pekerjaan yang Sudah Punah karena Teknologi”

The blending of two or more languages or linguistic subtypes in speech is known as code mixing. Code mixing widely used either in written or spoken language. Social media nowadays mostly use spoken form especially YouTube. The purposes of the research are to investigate the use of code mixing in Nessie Judge’s videos and try to describe the type of code mixing used by the youtuber. Descriptive qualitative method used to gain the data analysis. The code mixing then, analyzed into two types: intra sentential and intra lexical code mixing. Type of intra sentential then classified into three kinds: interrogative, declarative, and imperative. The intra sentential and intra lexical then classified into five levels: word, phrase, clause, idiom and baster. The result shows that there are 24 types of intra sentential and 1 type of intra lexical. From the sub type of sentential found 23 types of declarative, 1 interrogative, and no imperative type. While the level of code mixing found 12 words level, 5 phrases level, no idiom level, 8 clauses level, and 2 basters level.

Wine tasting notes as formulaic texts

The linguistic term “formulaic language” refers to fixed expressions or sequences of words that are often used as a single unit and are typically stored in memory and retrieved as complete units during communication, rather than being constructed or analyzed anew each time by the rules of grammar. Today, however, the concept of formulaicity has expanded beyond individual word combinations to include larger units as formulaic texts. In certain text genres such as abstracts and recipes, formulaicity is visible not only at the level of wording, but also in text content, structure, and layout. But it has not been examined in other text genres where professionals could benefit from this fixed structure in order to produce acceptable texts. In the present article we aim to analyze if wine tasting notes can be considered formulaic in nature. To meet our expectations, a corpus of wine tasting notes written originally in English will be used and collocations that help build up a text examined; by using Biel’s text-organizing patterns and term-embedding collocations, and by analyzing tasting notes in terms of Gülich’s criteria for formulaic texts, the present study will try to show if wine tasting notes are indeed formulaic. Our findings enhance dictionary entries by capturing the full spectrum of sensory experiences and professional terminology in oenology, improving lexical entries in both oenology and general monolingual dictionaries through the identification and categorization of formulaic language in wine tasting notes.

Critical discourse analysis of Martin Luther's speech

This study aims to critically examine Martin Luther’s speech through the lens of Critical Discourse Analysis (CDA), focusing on the interaction between language and societal factors such as race, social class, and identity. By analyse the speech at the word, text, social, and discursive levels, this research seeks to uncover the ways in which Luther’s rhetoric reflects and influences the socio-political context of his time. The study employs a descriptive and qualitative methodology, utilizing historical transcripts as the primary data source. At the micro-level, the analysis emphasizes lexical features and transitivity, while the macro-level analysis explores grammatical, social, ideological, and discursive characteristics. The findings reveal that Luther’s strategic use of language not only challenged the dominant ideologies of his era but also played a significant role in shaping the Reformation movement. The study concludes that Luther’s speech serves as a powerful example of how discourse can be used to both reflect and enact social change.