Attitude of Korean Speech-Language Pathologists toward Usage of Language Sample Analysis and Computer-aided LSA

이윤경,; 최지은,; 오소정,; 윤지혜,; 김유섭,

doi:10.12963/csd.20731

Cited by 4 publications

(1 citation statement)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Its characteristic is to quantify all words, so that the relationship between words can be measured quantitatively and the relationship between words can be excavated. The data set is selected from the Chinese and English parallel scientific and Technological Literature collected by the experiment [10]. Firstly, the monolingual word vector is normalized, and the orthogonal optimization of small dictionary word pair training set is simulated.…”

Section: Simulationsmentioning

confidence: 99%

A Cross Language Information Retrieval Model Based on Latent Semantic Analysis

2024

Advances in Transdisciplinary Engineering

View full text Add to dashboard Cite

Aiming at the problems of traditional query expansion methods, a cross language information retrieval scheme based on latent semantic analysis(LSA) was proposed. The method based on SVD and matrix decomposition was used to model wholeheartedly. Then, different types of information were introduced to the singular value decomposition process to analyze the local features and similarity of feature words. Finally, text clustering was applied to the interactive process of retrieval to improve the quality of information retrieval. The experimental results showed that the text retrieval strategy based on latent semantics proposed in this paper effectively improved and optimized the effect of cross language text classification and retrieval. Compared with the traditional algorithm, it had a great improvement in the accuracy index of retrieval.

show abstract

Section: Simulationsmentioning

confidence: 99%

A Cross Language Information Retrieval Model Based on Latent Semantic Analysis

2024

Advances in Transdisciplinary Engineering

View full text Add to dashboard Cite

show abstract

A Qualitative Study on Experiences and Needs of Language Sample Analysis by Speech–Language Pathologists: Focused on Children with Language Disorders

Oh¹,

Yoon²,

Lee³

2020

Commun Sci Disord

Self Cite

View full text Add to dashboard Cite

Objectives: Language sample analysis has been the "golden standard" in language assessment for children. The purpose of this study is to examine opinions of SLPs on their experiences with children's language analysis and to find alternatives that could make the analysis more useful and robust. Methods: Eight SLPs with experience in language sample analysis participated in in-depth interviews on the needs, implementation, and obstacles of language sample analysis in child language evaluation and intervention. Interviews were conducted individually with the first researcher based on the questionnaire developed by the researchers, and the interviews were recorded and transcribed and coded according to the qualitative research method. Results: As a result of qualitative analysis by transferring the contents of the interview, 2 topics and 8 sub-themes were derived for the current state of utterance analysis, and 4 topics for the alternatives to utterance analysis and 11 topics accordingly. Conclusion: All experts recognized the need for utterance analysis, but noted that there were practical difficulties in conducting utterance analysis in clinical settings. In order to properly realize the value of speech analysis in children's language evaluation, three things need to be developed; systematic sampling procedures, objective analysis using natural language processing technology, and norms and criteria through accumulation of sufficient language sample data for various age groups.

show abstract

Exploring Text Mining as a Vocabulary Evaluation Method: Focusing on Utterance Data from Children and Adolescents

Oh¹,

Yoon²,

Lee³

2022

Commun Sci Disord

View full text Add to dashboard Cite

Objectives: Recently, awareness of the need for computerized language analysis using natural language processing technology is increasing, but interest has been focused on morpheme analysis and automatic measurement. The purpose of this study is to explore the possibility of evaluating language samples, especially vocabulary, using the text mining method, which is one of the big data analysis methods.Methods: A total of 14 elementary and middle school students with typical development participated in conversations on topics such as family, school, and hobbies; and the utterances collected in the conversation were analyzed by group, using web-based text-mining program for 1) frequency analysis and word cloud, 2) semantic network analysis based on connection centrality, 3) CONCOR analysis that clusters topics based on meaning. Then, the utterances of two children in each group were individually analyzed with the same procedure.Results: In the vocabulary cloud of elementary school and middle school students’ group data, family names and school-related vocabulary appeared as top words, and topics such as daily routine, family time, relatives and holidays were clustered. By presenting the visualized result using the text mining method, it was possible to intuitively grasp the content. It was possible to understand the relationship between the vocabularies in order to understand the overall content structure.Conclusion: Text mining methods were confirmed to be viable tools for individualized and qualitative vocabulary evaluation and a supplement the traditional vocabulary evaluation method.

show abstract

Attitude of Korean Speech-Language Pathologists toward Usage of Language Sample Analysis and Computer-aided LSA

Cited by 4 publications

References 17 publications

A Cross Language Information Retrieval Model Based on Latent Semantic Analysis

A Cross Language Information Retrieval Model Based on Latent Semantic Analysis

A Qualitative Study on Experiences and Needs of Language Sample Analysis by Speech–Language Pathologists: Focused on Children with Language Disorders

Exploring Text Mining as a Vocabulary Evaluation Method: Focusing on Utterance Data from Children and Adolescents

Contact Info

Product

Resources

About