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Journal of Speech, Language, and... Feb 2021Purpose Prior studies report conflicting descriptions of the relationships between phonological awareness (PA), vocabulary, and speech perception in preschoolers with...
Purpose Prior studies report conflicting descriptions of the relationships between phonological awareness (PA), vocabulary, and speech perception in preschoolers with speech disorders. This study sought to determine the nature of these relationships in a sample of school-aged children with residual speech sound errors affecting /ɹ/. Method Participants included 110 children aged 7;0-17;4 (years;months) with residual errors impacting /ɹ/. Data on perceptual acuity and perceptual bias in an /ɹ/ identification task, receptive vocabulary, and PA were obtained. A theoretically and empirically motivated path model was constructed with vocabulary mediating the relationship between two measures of speech perception and PA. Model parameters were determined through maximum likelihood estimation with standard errors that were robust to nonnormality. Monte Carlo simulation was used to examine achieved power at the current sample size. Results The saturated path model explained 19% of the variance in PA. The direct path between age-adjusted perceptual acuity and PA was significant, as was the direct path between vocabulary and PA. Contrary to our hypothesis, there was no evidence in the current sample that vocabulary skill mediated the relationship between speech perception and PA. Each individual path was adequately powered at the current sample size. Conclusions The overall model provided evidence for a continued relationship between speech perception, measured by perceptual acuity of the sound in error, and PA in school-aged children with residual speech errors. Thus, measures of speech perception remain relevant to the assessment of school-aged children and adolescents in this population. Supplemental Material https://doi.org/10.23641/asha.13641275.
Topics: Adolescent; Child; Humans; Phonetics; Schools; Speech Perception; Speech Sound Disorder; Vocabulary
PubMed: 33514264
DOI: 10.1044/2020_JSLHR-20-00356 -
Infancy : the Official Journal of the... 2023Early screening for language problems is a priority given the importance of language for success in school and interpersonal relationships. The paucity of reliable...
Early screening for language problems is a priority given the importance of language for success in school and interpersonal relationships. The paucity of reliable behavioral instruments for this age group prompted the development of a new touchscreen language screener for 2-year-olds that relies on language comprehension. Developmental literature guided selection of age-appropriate markers of language disorder risk that are culturally and dialectally neutral and could be reliably assessed. Items extend beyond products of linguistic knowledge (vocabulary and syntax) and tap the process by which children learn language, also known as fast mapping. After piloting an extensive set of items (139), two phases of testing with over 500 children aged 2; 0-2; 11 were conducted to choose the final 40-item set. Rasch analysis was used to select the best fitting and least redundant items. Norms were created based on 270 children. Sufficient test-retest reliability, Cronbach's alpha, and convergent validity with the MB-CDI and PPVT are reported. This quick behavioral measure of language capabilities could support research studies and facilitate the early detection of language problems.
Topics: Child; Humans; Child, Preschool; Reproducibility of Results; Language; Vocabulary; Learning
PubMed: 37350307
DOI: 10.1111/infa.12554 -
Journal of Deaf Studies and Deaf... Dec 2023Studies have shown the benefits of fingerspelling on literacy skills in school-age deaf and hard-of-hearing students. This study is an observation of 20 first- and...
Studies have shown the benefits of fingerspelling on literacy skills in school-age deaf and hard-of-hearing students. This study is an observation of 20 first- and second-grade classrooms. The classroom observations were coded for fingerspelling event frequency, type, length, and whether it was chained to print. The observations showed that teachers used an average of 54 fingerspelled events during 40-min lessons. Teachers' frequency of fingerspelling was positively related to students' frequency of fingerspelling. The types of words fingerspelled included Vocabulary (nouns, verbs, adjectives, and adverbs), Function (prepositions, articles, and conjunctions), Abbreviations, and Single Letter Names (i.e., manual alphabet). Teachers most frequently fingerspelled Vocabulary words (57.9%, SD = 22.1%) followed by Function words (15%, SD = 11.2%). The average length of Vocabulary and Function words were 4.2 (SD = 0.7) and 2.9 (SD = 1.1) letters, respectively. Teachers chained fingerspelling to print 20% (SD = 10%) of the time. We suggest that teachers could increase and more systematically use fingerspelling in early-elementary classrooms, explicitly bridging the connection between fingerspelling and print given its association with reading.
Topics: Humans; Persons With Hearing Impairments; Language; Hearing Loss; Vocabulary; Deafness; Reading
PubMed: 37462230
DOI: 10.1093/deafed/enad023 -
Journal of Speech, Language, and... Sep 2021Purpose Language is an important skill required for children to succeed in school. Higher language skills are associated with school readiness in young children and...
Purpose Language is an important skill required for children to succeed in school. Higher language skills are associated with school readiness in young children and general mathematics performance. However, many students with mathematics difficulty (MD) may be more likely to present difficulties with language skills than their peers. The purpose of this report was to compare the language performance of children with and without MD. Method We compared child vocabulary, morphology, and syntax between first- and second-grade children ( = 247) classified as with or without MD, controlling for child working memory. Results Children with MD ( = 119) significantly underperformed compared with their peers ( = 155) on all language measures. The largest difference between children with and without MD was in syntax. Conclusions Children with MD present poorer language skills than their peers, which aligns with previous research linking the importance of syntax with mathematics learning. More research is needed to better understand the complex links between language skills and mathematical development.
Topics: Aptitude; Child; Child, Preschool; Humans; Language; Mathematics; Memory, Short-Term; Vocabulary
PubMed: 34310199
DOI: 10.1044/2021_JSLHR-20-00378 -
Scientific Reports Feb 2023Rhythmic skills have been repeatedly found to relate to children's early literacy skills. Using rhythmic tasks to predict language and reading performance seems a...
Rhythmic skills have been repeatedly found to relate to children's early literacy skills. Using rhythmic tasks to predict language and reading performance seems a promising direction as they can be easily administered early as a screening test to identify at-risk children. In the present study, we measured Hungarian children's (N = 37) general cognitive abilities (working memory, non-verbal reasoning and rapid automatized naming), language and literacy skills (vocabulary, word reading, phonological awareness and spelling) and finger tapping performance in a longitudinal design in the first and third grades. We applied metronome stimuli in three tempi (80, 120, 150 bpm) using a synchronization-continuation paradigm and also measured participants' spontaneous motor tempo. While children's synchronization asynchrony was lower in third than in the first grade, with the exception of the slow-tempo trials, tapping consistency and continuation tapping success showed no development in this period. First-year tapping consistency in the slow-tempo tasks was associated with third-year reading and spelling outcomes. Our results show that the relation between tapping performance and literacy skills persists throughout the third school year, making the sensorimotor synchronization task a potentially effective instrument for predicting literacy outcomes, and a useful tool for early screening of reading difficulties.
Topics: Humans; Child; Literacy; Reading; Language; Vocabulary; Schools
PubMed: 36759633
DOI: 10.1038/s41598-023-29367-5 -
Journal of Autism and Developmental... Apr 2023This longitudinal study examined how receptive and expressive vocabulary assessments capture vocabulary development in children with Autism Spectrum Disorder (ASD) and...
This longitudinal study examined how receptive and expressive vocabulary assessments capture vocabulary development in children with Autism Spectrum Disorder (ASD) and typically developing (TD) children. Using mixed regression modelling, we explored when children with ASD significantly different from TD children. We also examined the variability of individual trajectories of vocabulary development in children with ASD. Children with ASD showed slowed trajectories and significantly differed from TD children by 24 months on all assessments except for picture-based assessments. Children with ASD also showed high heterogeneity in trajectories, with some showing inconsistent patterns of growth, stagnation, and regression across assessments. This suggests that conclusions based on individual assessments of vocabulary can vary and assessment characteristics must be considered when monitoring vocabulary development.
Topics: Child; Humans; Autism Spectrum Disorder; Vocabulary; Longitudinal Studies; Child Development
PubMed: 34817769
DOI: 10.1007/s10803-021-05379-w -
Journal of Experimental Child Psychology Jun 2021The disambiguation effect, also referred to as process of elimination, occurs during word learning, whereby novel words are mapped onto new referents, precluding the...
The disambiguation effect, also referred to as process of elimination, occurs during word learning, whereby novel words are mapped onto new referents, precluding the application of a novel label to a familiar object. Prior studies showed that the emergence and use of disambiguation can be affected by children's vocabulary growth and linguistic experience, such as growing up with more than one language. To test this, we investigated (a) whether monolingual and multilingual children disambiguated a novel word-object mapping, (b) whether they retained a trained, previously seen word-object mapping, (c) whether they retained the novel fast-mapped word-object mapping, and (d) whether and how age, English vocabulary size, and language background modulated disambiguation and retention. Lastly, we tested (e) whether children who disambiguated also retained better. Eye-tracking data from 18- to 30-month-old monolingual children (n = 43) and multilingual children (n = 40) were collected. A looking-while-listening paradigm with two objects included two familiar items, one novel item, and one trained item. Mixed-effect models reported that vocabulary size predicted the outcome of mapping and retention better than age. Monolingual children's accuracy on disambiguation trials was high from the start, whereas multilingual children started to disambiguate later as their vocabulary grew. Only monolingual children performed above chance level on retaining the novel label. Lastly, the use of disambiguation improved retention for monolingual children but not for multilingual children. This research corroborates that disambiguation should be regarded as a mechanism facilitating default fast mapping rather than fully fledged learning. Vocabulary growth leading to an increase in disambiguation supports the notion that the disambiguation effect stems from prior episodes of learning.
Topics: Child; Child, Preschool; Eye-Tracking Technology; Humans; Infant; Language; Language Development; Multilingualism; Verbal Learning; Vocabulary
PubMed: 33582226
DOI: 10.1016/j.jecp.2020.105072 -
PloS One 2024To help non-native English speakers quickly master English vocabulary, and improve reading, writing, listening and speaking skills, and communication skills, this study...
To help non-native English speakers quickly master English vocabulary, and improve reading, writing, listening and speaking skills, and communication skills, this study designs, constructs, and improves an English vocabulary learning model that integrates Spiking Neural Network (SNN) and Convolutional Long Short-Term Memory (Conv LSTM) algorithms. The fusion of SNN and Conv LSTM algorithm can fully utilize the advantages of SNN in processing temporal information and Conv LSTM in sequence data modeling, and implement a fusion model that performs well in English vocabulary learning. By adding information transfer and interaction modules, the feature learning and the timing information processing are optimized to improve the vocabulary learning ability of the model in different text contents. The training set used in this study is an open data set from the WordNet and Oxford English Corpus data corpora. The model is presented as a computer program and applied to an English learning application program, an online vocabulary learning platform, or a language education software. The experiment will use the open data set to generate a test set with text volume ranging from 100 to 4000. The performance indicators of the proposed fusion model are compared with those of five traditional models and applied to the latest vocabulary exercises. From the perspective of learners, 10 kinds of model accuracy, loss, polysemy processing accuracy, training time, syntactic structure capturing accuracy, vocabulary coverage, F1-score, context understanding accuracy, word sense disambiguation accuracy, and word order relation processing accuracy are considered. The experimental results reveal that the performance of the fusion model is better under different text sizes. In the range of 100-400 text volume, the accuracy is 0.75-0.77, the loss is less than 0.45, the F1-score is greater than 0.75, the training time is within 300s, and the other performance indicators are more than 65%; In the range of 500-1000 text volume, the accuracy is 0.81-0.83, the loss is not more than 0.40, the F1-score is not less than 0.78, the training time is within 400s, and the other performance indicators are above 70%; In the range of 1500-3000 text volume, the accuracy is 0.82-0.84, the loss is less than 0.28, the F1-score is not less than 0.78, the training time is within 600s, and the remaining performance indicators are higher than 70%. The fusion model can adapt to various types of questions in practical application. After the evaluation of professional teachers, the average scores of the choice, filling-in-the-blank, spelling, matching, exercises, and synonyms are 85.72, 89.45, 80.31, 92.15, 87.62, and 78.94, which are much higher than other traditional models. This shows that as text volume increases, the performance of the fusion model is gradually improved, indicating higher accuracy and lower loss. At the same time, in practical application, the fusion model proposed in this study has a good effect on English learning tasks and offers greater benefits for people unfamiliar with English vocabulary structure, grammar, and question types. This study aims to provide efficient and accurate natural language processing tools to help non-native English speakers understand and apply language more easily, and improve English vocabulary learning and comprehension.
Topics: Humans; Vocabulary; Memory, Short-Term; Language; Neural Networks, Computer; Algorithms
PubMed: 38517859
DOI: 10.1371/journal.pone.0299425 -
Computer Methods and Programs in... Aug 2021The growing integration of healthcare sources is improving our understanding of diseases. Cross-mapping resources such as UMLS play a very important role in this area,...
BACKGROUND AND OBJECTIVES
The growing integration of healthcare sources is improving our understanding of diseases. Cross-mapping resources such as UMLS play a very important role in this area, but their coverage is still incomplete. With the aim to facilitate the integration and interoperability of biological, clinical and literary sources in studies of diseases, we built DisMaNET, a system to cross-map terms from disease vocabularies by leveraging the power and interpretability of network analysis.
METHODS
First, we collected and normalized data from 8 disease vocabularies and mapping sources to generate our datasets. Next, we built DisMaNET by integrating the generated datasets into a Neo4j graph database. Then we exploited the query mechanisms of Neo4j to cross-map disease terms of different vocabularies with a relevance score metric and contrasted the results with some state-of-the-art solutions. Finally, we made our system publicly available for its exploitation and evaluation both through a graphical user interface and REST APIs.
RESULTS
DisMaNET contains almost half a million nodes and near nine hundred thousand edges, including hierarchical and mapping relationships. Its query capabilities enabled the detection of connections between disease vocabularies that are not present in major mapping sources such as UMLS and the Disease Ontology, even for rare diseases. Furthermore, DisMaNET was capable of obtaining more than 80% of the mappings with UMLS reported in MonDO and DisGeNET, and it was successfully exploited to resolve the missing mappings in the DISNET project.
CONCLUSIONS
DisMaNET is a powerful, intuitive and publicly available system to cross-map terms from different disease vocabularies. Our study proves that it is a competitive alternative to existing mapping systems, incorporating the potential of network analysis and the interpretability of the results through a visual interface as its main advantages. Expansion with new sources, versioning and the improvement of the search and scoring algorithms are envisioned as future lines of work.
Topics: Algorithms; Databases, Factual; Vocabulary; Vocabulary, Controlled
PubMed: 34157517
DOI: 10.1016/j.cmpb.2021.106233 -
Journal of Speech, Language, and... Feb 2022This study aimed to examine how speech while sign (simultaneous communication [SimCom]) affects the spoken language of bimodal bilingual teachers and how individual...
PURPOSE
This study aimed to examine how speech while sign (simultaneous communication [SimCom]) affects the spoken language of bimodal bilingual teachers and how individual differences in sign-language vocabulary knowledge, SimCom teaching experience, and the ability to perform speech under dual-task conditions explain the variability in SimCom performance.
METHOD
Forty experienced teachers of deaf and hard of hearing students participated in a story narration task under different conditions. Speech rate, lexical richness, and syntactic complexity were measured and compared across speech-only versus SimCom conditions. Furthermore, participants' score on a sign-language vocabulary test, their self-reported SimCom teaching experience, and their performance in a dual-task condition were taken as predictors of SimCom narration performance.
RESULTS
The findings revealed slower speech rate, lower lexical richness, and lower syntactic complexity in the SimCom condition compared with the speech-only condition. Sign-language vocabulary score and SimCom teaching experience explained speech rate and lexical richness. Participant's ability to speak under a dual-task condition did not modulate performance.
CONCLUSIONS
The findings may suggest that the production of the less dominant (sign) language during SimCom entails inhibition of the dominant (spoken) language relative to the speech-only condition. At the same time, the findings are also compatible with the suggestion that SimCom serves as a unique complex communication unit that cannot be reduced to the combination of two languages.
Topics: Communication; Humans; Language; Language Tests; Sign Language; Vocabulary
PubMed: 35050718
DOI: 10.1044/2021_JSLHR-21-00326