• Journal of Digital Convergence
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• v.19 no.7
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• pp.199-208
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• 2021

Automatic Post Editing(APE) is the study that automatically correcting errors included in the machine translated sentences. The goal of APE task is to generate error correcting models that improve translation quality, regardless of the translation system. For training these models, source sentence, machine translation, and post edit, which is manually edited by human translator, are utilized. Especially in the recent APE research, multilingual pretrained language models are being adopted, prior to the training by APE data. This study deals with multilingual pretrained language models adopted to the latest APE researches, and the specific application method for each APE study. Furthermore, based on the current research trend, we propose future research directions utilizing translation model or mBART model.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.489-495
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• 2022

It makes difference to LSTM D/L(Deep Learning) results for language model construction as the corpus preprocess changes. An LSTM model was trained with a famouse literaure poems(Ki Hyung-do's work) for training corpus in the study. You get the two wordvector sets for two corpus sets of the original text and eraised word ending text each once D/L training completed. It's been inspected of the similarity/analogy operation results, the positions of the wordvectors in 2D plane and the generated texts by the language models for the two different corpus sets. The suggested words by the silmilarity/analogy operations are changed for the corpus sets but they are related well considering the corpus characteristics as a literature work. The positions of the wordvectors are different for each corpus sets but the words sustained the basic meanings and the generated texts are different for each corpus sets also but they have the taste of the original style. It's supposed that the D/L language model can be a useful tool to enjoy the literature in object and in diverse with the analysis results shown in the study.

• Journal of Korean society of Dental Hygiene
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• v.22 no.5
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• pp.375-382
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• 2022

Objectives: This study analyzes factors related to English communication skills in the dental health services of clinical dental hygienists who provide dental medical services to foreigners. Methods: Surveys were conducted to measure students' English communication skills. Participants comprised 195 clinical dental hygienists working at dental English study cafes or who provided dental medical services to foreigners. After analyzing the differences in English communication skills, hierarchical multiple regression analysis was performed on the factors related to English communication skills. Results: English communication skill of dental hygienists was 1.96 points out of 5 points. The factors related to the English communication skill of the clinical dental hygienists were foreign patient care, language training experience, overseas living experience, and certified English proficiency. The adjusted explanatory power of this model was 53.0%. Conclusions: Dental hygienists in charge of foreign patients have experience in language training and overseas residence, have a language qualification certificate, and have higher English communication skills. It is necessary to develop English language learning programs based on metaverse to develop the English communication skills of dental hygienists who provide dental health services to foreign patients and to operate a creative educational environment to increase interest in learning English.

• The Journal of Korean Physical Therapy
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• v.22 no.5
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• pp.109-115
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• 2010

Purpose: This study was to delineate the structural change of neural pathway after sequential motor learning using diffusion tensor imaging (DTI). Methods: The participants were 16 healthy subjects, which were divided by training (n=8) and control (n=8) group. The task for the training was the Serial Reaction Time Task (SRTT) which was designed by Superlab program. When the 'asterisk' shows up in the 4 partition spaces on the monitor, the subject presses the correct response button as soon as possible. The training group participated in the training program of motor learning with SRTT composed of 24 digits pattern in one hour per daily through 10 days during 2 weeks. Results: In the behavioral results the training group showed significant changes in the increase of response number and the reduction of response time than those of the control group. There was significant difference in the left inferior frontal area in the fractional anisotropy (FA) map of the training group in DTI analysis. Conclusion: Motor sequential learning as like SRTT may be needed to the learning of language and visuospatial processing and may be induced for the experience-dependent structural plasticity during short period.

• Journal of Digital Convergence
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• v.14 no.3
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• pp.299-307
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• 2016

This Convergence study aimed to investigate the effects of changing brainwave neurofeedback training on life stress and depression in female college students. Twenty-six of the subjects were selected into the experimental group and the control group respectively intervention for 8 weeks, the following results were obtained. First, experimental group and control group presented statistical significant difference before and after intervention on life stress, and life stress in experimental group was statistical significantly decreased than control group. Second, experimental group and control group presented statistical significant difference before and after intervention on depression, and depression in experimental group was statistically significantly decreased than control group. The results obtained from this study expect us that applying the neurofeedback training for the decrease of life stress and depression, has a positive effect.

• Journal of Digital Convergence
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• v.13 no.9
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• pp.361-368
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• 2015

This research aimed to investigate the effects of neurofeedback training on unilateral neglect and depression in patients with stroke. Fourteen of the subjects were selected from the experimental group and the control group respectively; the following results were obtained. First, experimental group and the control group presented significant statistical difference before and after intervention on neglect. However, there is after intervention no significant statistical among them. Two, experimental group and the control group presented significant statistical difference before and after intervention on depression, and the experimental group demonstrated more decrease than the control group in depression. The results obtained from this research expect us that applying the neurofeedback training for the improvement of neglect and depression, to stroke patients has a positive effect on the rehabilitation of patients.

• The KIPS Transactions:PartD
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• v.12D no.1 s.97
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• pp.159-164
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• 2005

In a computing environment connected pan-based computers and a server by Internet, This paper describes a language learning system evaluating the quality of a handwriting string. For the purpose of the system, this paper explains how to retrieve reference data from a database, how to evaluate the quality of a handwriting string using global and local features. The Proposed system can evaluate the qualify of a handwriting string as well as a handwriting character. The qualify can be computed in the case of different language between reference and input. Therefore, we expect that the system is very useful not only for training on handwriting but also learning a language.

• Journal of Information Technology Applications and Management
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• v.21 no.3
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• pp.65-77
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• 2014

Ubiquitous learning has aroused great interest and is becoming a new way for foreign language education in today's society. However, how to increase the learners' initiative and their community cohesion is still an issue that deserves more profound research and studies. Emotional intelligence can help to detect the learner's emotional reactions online, and therefore stimulate his interest and the willingness to participate by adjusting teaching skills and creating fun experiences in learning. This is, actually the new concept of smart education. Based on the previous research, this paper concluded a neural mechanism model for analyzing the learners' emotional characteristics in ubiquitous environment, and discussed the intelligent monitoring and automatic recognition of emotions from the learners' speech signals as well as their behavior data by multi-agent system. Finally, a framework of emotional intelligence system was proposed concerning the smart foreign language education in ubiquitous learning.

• Journal of Korean language education
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• v.28 no.1
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• pp.251-268
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• 2017

This study is based on differences of syllable type between Korean and Chinese language pronunciation. For example, Nasal consonant ending 【n】 and 【${\eta}$】 reside in both Korean and Chinese phonetics simultaneously. However, in experiential training, Chinese learners will make errors in pronunciation of the Korean syllable nasal consonant ending like 【n】 and 【${\eta}$】. In the previous research, analysis of pronunciation errors were often based on the perspective of phonological system and combination of the phoneme rules. However, in this study, the analysis is based on the differences between Korean and Chinese syllables category to indicate the cause of pronunciation errors. The main findings of this study indicated that in the process of pronunciation of Chinese, nasal consonant syllable rime and its 【back】 tongue vowel are combined with each other. However, this rule does not apply in Korean pronunciation. Therefore, the Korean syllabic types like "앤, 응, 옹, 앵, 은, 온, 언" also exist in the Chinese language. When theChinese learners pronounce these types of syllables, the combination of the voweland nasal syllable rime rule will be taken, which will result in pronunciationerrors.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.369-376
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• 2021

One of the most active areas of research in the field of affective computing and signal processing is emotion recognition. This paper proposes emotion recognition of low-resource (Sindhi) language. This work's uniqueness is that it examines the emotions of languages for which there is currently no publicly accessible dataset. The proposed effort has provided a dataset named MAVDESS (Mehran Audio-Visual Dataset Mehran Audio-Visual Database of Emotional Speech in Sindhi) for the academic community of a significant Sindhi language that is mainly spoken in Pakistan; however, no generic data for such languages is accessible in machine learning except few. Furthermore, the analysis of various emotions of Sindhi language in MAVDESS has been carried out to annotate the emotions using line features such as pitch, volume, and base, as well as toolkits such as OpenSmile, Scikit-Learn, and some important classification schemes such as LR, SVC, DT, and KNN, which will be further classified and computed to the machine via Python language for training a machine. Meanwhile, the dataset can be accessed in future via https://doi.org/10.5281/zenodo.5213073.