A New Formula for Vietnamese Text Readability Assessment

Luong, An-Vinh; Nguyen, Diep; Đinh, Điền

doi:10.1109/kse.2018.8573379

Cited by 6 publications

(8 citation statements)

References 3 publications

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“…Meanwhile, the experimentation using the two formulas of Nguyen and Henkin [11,17] on the set of readings in Vietnamese textbooks and Literature in Vietnam at the present yielded the correlation results of only about 0.51 and 0.58, respectively. When we updated the weights of Nguyen and Henkin's formulas [11,17] and Luong, et al [18] using our corpus, the correlation with the text readability increased, but it was not as high as the result in our first experiment.…”

Section: ) Statistical Approachmentioning

confidence: 76%

“…This approach has been implemented in a broad range of studies, including but not limited to Chall and Dale [2], Kincaid, et al [14], Zeno, et al [15], as well as Lee and Hasebe [16]. In Vietnamese, there have been four studies based on this approach: three of which are by Nguyen and Henkin [17], Nguyen and Henkin [11], Luong, et al [18], and one of which is by Nguyễn, et al [19]. Meanwhile, in the machine learning approach, features are included in machine learning classifiers to evaluate which features help increase the accuracy of the classification process.…”

Section: Related Workmentioning

confidence: 99%

“…Table V and Table VI present the intercept scores the coefficients of the features in the estimation equation after regression analysis of both experiments. Table VII shows the correlation of the two estimation equations in our experiments with the text difficulty along with (i) the most correlated feature in our experiment (average word set rankings), (ii) the two text readability measurement formulas of Nguyen and Henkin [11,17] and their revised version on our experiment corpus, and (iii) the revised version of the formula of Luong, et al [18]. The correlations of the estimation equations with the text difficulty of the first experiment, the second experiment, and the highest feature (average word set rankings) were 0.95, 0.92 and 0.91, respectively.…”

Section: ) Statistical Approachmentioning

confidence: 99%

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Assessing Vietnamese Text Readability using Multi-Level Linguistic Features

Luong¹,

Nguyen²,

Đinh³

et al. 2020

IJACSA

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Text readability is the problem of determining whether a text is suitable for a certain group of readers, and thus building a model to assess the readability of text yields great significance across the disciplines of science, publishing, and education. While text readability has attracted attention since the late nineteenth century for English and other popular languages, it remains relatively underexplored in Vietnamese. Previous studies on this topic in Vietnamese have only focused on the examination of shallow word-level features using surface statistics such as frequency and ratio. Hence, features at higher levels like sentence structure and meaning are still untapped. In this study, we propose the most comprehensive analysis of Vietnamese text readability to date, targeting features at all linguistic levels, ranging from the lexical and phrasal elements to syntactic and semantic factors. This work pioneers the investigation on the effects of multi-level linguistic features on text readability in the Vietnamese language.

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Section: ) Statistical Approachmentioning

confidence: 76%

Section: Related Workmentioning

confidence: 99%

Section: ) Statistical Approachmentioning

confidence: 99%

See 1 more Smart Citation

Assessing Vietnamese Text Readability using Multi-Level Linguistic Features

Luong¹,

Nguyen²,

Đinh³

et al. 2020

IJACSA

Self Cite

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show abstract

“…In [25] the authors proposed a readability formula that focused on the number of words in a sentence and the number of sentences in 300 words in a given text. In [26] the authors devised a formula for determining the readability of Vietnamese text which took into account the average sentence length in characters, the average of word length in terms of the number of characters, and the percentage of difficult words that was calculated using a list of easy words.…”

Section: Lexical Parametersmentioning

confidence: 99%

Revisiting the Role of Classical Readability Formulae Parameters in Complex Word Identification (Part 2)

Venugopal¹,

Pramod²,

Saini³

2022

CSJM

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Accessibility of text is an attribute that deserves the attention of researchers and content creators. This study is an attempt to determine the lexical features that play a key role in identifying complex words in Hindi text. As the first step, we studied the parameters used in readability metrics in different languages and tested their importance on classifiers built on datasets created with the help of a user study. In part of the study, we reported the results of two different approaches used to label a word as complex. In this part, we compare the previous results with the results obtained from a third labeling approach. We found satisfactory evidence for certain parameters and also observed a new parameter that could be used while devising readability metrics for Hindi.

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“…Furthermore, 30 other passages were additionally used to evaluate this formula [9]. In the recent studies on Vietnamese text readability, Luong et al [10,12,11], Diep et al [13] examined around 380 texts collected from school textbooks to examine the effect of the text length and some specific Vietnamese language features on the text readability. In recent years, along with the process of the education reforms, the issue of assessing the readability of the text has received more attention.…”

Section: Introductionmentioning

confidence: 99%

Building a Corpus for Vietnamese Text Readability Assessment in The Literature Domain

Luong¹,

Nguyen²,

Đinh³

2020

ujer

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Text readability is a measure of how easy or difficult it is to read a text. This readability factor plays a crucial role in the processes of drafting and comprehending the texts, affecting the choice of proper texts for reading. Studies on the readability of text have started since the late nineteenth century and there have been many practical applications. However, these studies are mainly performed in English and other popular languages. In Vietnamese, the study of the text readability is still relatively untapped and has only received attention in recent years in the process of improving the curriculum and teaching methods. Recent studies on the readability of text in Vietnamese language are still limited, the main reason was largely due to the lack of text resources, which are corpora graded accordingly to difficulty levels. Therefore, in this study, we focused on building a corpus for assessing the readability of Vietnamese texts in the literature domain through the process of collecting, processing and evaluating documents. The result is that we have built up a corpus of 1,825 Vietnamese texts, divided into four levels of difficulty (Very easy, Easy, Medium and Difficult). Experiments with the existing Vietnamese readability assessment methods show that the built corpus is reliable and usable for further research on the text readability.

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A New Formula for Vietnamese Text Readability Assessment

Cited by 6 publications

References 3 publications

Assessing Vietnamese Text Readability using Multi-Level Linguistic Features

Assessing Vietnamese Text Readability using Multi-Level Linguistic Features

Revisiting the Role of Classical Readability Formulae Parameters in Complex Word Identification (Part 2)

Building a Corpus for Vietnamese Text Readability Assessment in The Literature Domain

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