How is Samsung Lee Kun-hee Remembered? : Through the Language Analysis in the Newspaper Obituaries

2021 ◽  
Vol 110 ◽  
pp. 156-183
Author(s):  
Wan Soo Lee ◽  
Myungil Choi
Keyword(s):  
Language Analysis

The Elicited Language Analysis Procedure

1982 ◽  
Vol 13 (1) ◽  
pp. 37-41
Author(s):  
Larry J. Mattes
Keyword(s):  
Diagnostic Tool ◽  
Descriptive Analysis ◽  
Quality Measures ◽  
Analysis Procedure ◽  
Elicited Imitation ◽  
Response Quality ◽  
Semantic Relationships ◽  
Language Analysis

Elicited imitation tasks are frequently used as a diagnostic tool in evaluating children with communication handicaps. This article presents a scoring procedure that can be used to obtain an in-depth descriptive analysis of responses produced on elicited imitation tasks. The Elicited Language Analysis Procedure makes it possible to systematically evaluate responses in terms of both their syntactic and semantic relationships to the stimulus sentences presented by the examiner. Response quality measures are also included in the analysis procedure.

Developmental Sentence Scoring

1984 ◽  
Vol 15 (3) ◽  
pp. 154-168 ◽  
Author(s):  
Mary Ann Lively
Keyword(s):  
Expressive Language ◽  
Analysis Techniques ◽  
Language Analysis ◽  
Scoring Errors

Developmental Sentence Scoring (DSS) is a useful procedure for quantifying thegrammatic structure of children's expressive language. Like most language analysis techniques, however, DSS requires considerable study and practice to use it correctly and efficiently. Clinicians learning DSS tend to make many scoring errors at first and they display similar confusions and mistakes. This article identifies some of these common "problem" areas and provides scoring examples to assist clinicians in learning the DSS procedure.

Accuracy of Four Language Analysis Procedures Performed Automatically

2001 ◽  
Vol 10 (2) ◽  
pp. 180-188 ◽  
Author(s):  
Steven H. Long ◽  
Ron W. Channell
Keyword(s):  
Automatic Identification ◽  
Published Data ◽  
Typically Developing ◽  
Language Impaired ◽  
Productivity Data ◽  
Language Analysis ◽  
Word Classes ◽  
Human Coder ◽  
Impaired Children ◽  
Metalinguistic Skills

Most software for language analysis has relied on an interaction between the metalinguistic skills of a human coder and the calculating ability of the machine to produce reliable results. However, probabilistic parsing algorithms are now capable of highly accurate and completely automatic identification of grammatical word classes. The program Computerized Profiling combines a probabilistic parser with modules customized to produce four clinical grammatical analyses: MLU, LARSP, IPSyn, and DSS. The accuracy of these analyses was assessed on 69 language samples from typically developing, speech-impaired, and language-impaired children, 2 years 6 months to 7 years 10 months. Values obtained with human coding and by the software alone were compared. Results for all four analyses produced automatically were comparable to published data on the manual interrater reliability of these procedures. Clinical decisions based on cutoff scores and productivity data were little affected by the use of automatic rather than human-generated analyses. These findings bode well for future clinical and research use of automatic language analysis software.

Machine-Scored Syntax: Comparison of the CLAN Automatic Scoring Program to Manual Scoring

2020 ◽  
Vol 51 (2) ◽  
pp. 479-493
Author(s):  
Jenny A. Roberts ◽  
Evelyn P. Altenberg ◽  
Madison Hunter
Keyword(s):  
Data Exchange ◽  
Child Language ◽  
Exchange System ◽  
Absolute Point ◽  
Language Analysis ◽  
Search Patterns ◽  
Language Data ◽  
Report Accuracy ◽  
Point To Point ◽  
Automatic Scoring

Purpose The results of automatic machine scoring of the Index of Productive Syntax from the Computerized Language ANalysis (CLAN) tools of the Child Language Data Exchange System of TalkBank (MacWhinney, 2000) were compared to manual scoring to determine the accuracy of the machine-scored method. Method Twenty transcripts of 10 children from archival data of the Weismer Corpus from the Child Language Data Exchange System at 30 and 42 months were examined. Measures of absolute point difference and point-to-point accuracy were compared, as well as points erroneously given and missed. Two new measures for evaluating automatic scoring of the Index of Productive Syntax were introduced: Machine Item Accuracy (MIA) and Cascade Failure Rate— these measures further analyze points erroneously given and missed. Differences in total scores, subscale scores, and individual structures were also reported. Results Mean absolute point difference between machine and hand scoring was 3.65, point-to-point agreement was 72.6%, and MIA was 74.9%. There were large differences in subscales, with Noun Phrase and Verb Phrase subscales generally providing greater accuracy and agreement than Question/Negation and Sentence Structures subscales. There were significantly more erroneous than missed items in machine scoring, attributed to problems of mistagging of elements, imprecise search patterns, and other errors. Cascade failure resulted in an average of 4.65 points lost per transcript. Conclusions The CLAN program showed relatively inaccurate outcomes in comparison to manual scoring on both traditional and new measures of accuracy. Recommendations for improvement of the program include accounting for second exemplar violations and applying cascaded credit, among other suggestions. It was proposed that research on machine-scored syntax routinely report accuracy measures detailing erroneous and missed scores, including MIA, so that researchers and clinicians are aware of the limitations of a machine-scoring program. Supplemental Material https://doi.org/10.23641/asha.11984364

How much Artistic Freedom is permitted when it comes to Language? - Analysis of a Crime Novel

2018 ◽  
Vol 5 (2) ◽  
pp. 50-60
Author(s):  
Manuela Svoboda ◽  
Petra Zagar-Sostaric
Keyword(s):  
Foreign Language ◽  
German Language ◽  
Direct Speech ◽  
Small Talk ◽  
Language Analysis ◽  
Crime Novel ◽  
Blood Relative ◽  
German Origin ◽  
Artistic Freedom ◽  
The One

Abstract In this article a closer look will be taken at the issue of inaccurately using a foreign language, i.e. German in this particular case, in a crime novel or thriller. Of course, in fiction the author has complete artistic freedom to invent and present things as he/she intends and it doesn`t necessarily have to be realistic or legitimate. But what happens when it comes to an existing language being quoted in fiction? For this purpose David Thomas’ thriller “Blood Relative - How well do you know the one you love?” is analysed regarding parts in which German quotes are used. As the plot is located partly in England and partly in former East Germany (GDR) and the protagonist’s wife is of German origin, direct speech, titles and names are used in German. Subsequently, they are translated into English by the author in order to be understood by the English reader. However, there are many grammar, spelling and semantic mistakes in these German expressions and common small talk quotes. This begs the question, is it justified to disregard linguistic correctness with regards to artistic freedom given the fact that we are dealing with a fictional thriller, or is it nevertheless necessary to be precise concerning foreign language usage? How far may one “test” their artistic freedom in this particular case? In order to answer these questions a detailed analysis of the thriller is performed, concerning artistic freedom and modern literature/light fiction as well as the German language used in quotes and direct speech.

FIGURATIVE LANGUAGE ANALYSIS ON THE UGLY LOVE NOVEL BY COLLEEN HOOVER

2019 ◽  
Vol 7 (2) ◽  
pp. 80-89
Author(s):  
Arini Egi Tiarawati ◽  
Tri Wahyu Retno Ningsih
Keyword(s):  
Qualitative Method ◽  
Figurative Language ◽  
Language Theory ◽  
The Novel ◽  
Dominant Type ◽  
Language Analysis ◽  
Descriptive Qualitative

The aim of this study is to analyze the types of figurative language which found in Ugly Love novel by Colleen Hoover. This study used figurative language theory by Leech to analyze the data which the researcher found in the novel. The method of this study is descriptive qualitative method. The total of the data are 87 data to be analyzed in the types of figurative language. The data will be identify and classify into 8 types of figurative language by Leech. The result of this study found 6 types of figurative language in this Ugly Love novel. That are 33 data of personifications (33 data) , 19 data of similes, 11 data of irony, 10 data of hyperbole, 9 data of metaphors, and 5 data of metonymy. The most of dominant type of figurative language in the Ugly Love novel by Colleen Hoover is personification.

Sign in / Sign up

Export Citation Format

Share Document