• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.29-35
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• 2020

In this paper, we propose a new structured entity recognition DeNERT model. Recently, the field of natural language processing has been actively researched using pre-trained language representation models with a large amount of corpus. In particular, the named entity recognition, which is one of the fields of natural language processing, uses a supervised learning method, which requires a large amount of training dataset and computation. Reinforcement learning is a method that learns through trial and error experience without initial data and is closer to the process of human learning than other machine learning methodologies and is not much applied to the field of natural language processing yet. It is often used in simulation environments such as Atari games and AlphaGo. BERT is a general-purpose language model developed by Google that is pre-trained on large corpus and computational quantities. Recently, it is a language model that shows high performance in the field of natural language processing research and shows high accuracy in many downstream tasks of natural language processing. In this paper, we propose a new named entity recognition DeNERT model using two deep learning models, DQN and BERT. The proposed model is trained by creating a learning environment of reinforcement learning model based on language expression which is the advantage of the general language model. The DeNERT model trained in this way is a faster inference time and higher performance model with a small amount of training dataset. Also, we validate the performance of our model's named entity recognition performance through experiments.

• Speech Sciences
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• v.8 no.4
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• pp.119-129
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• 2001

Language is one aspect of cognition, along with attention and concentration, learning and memory, visuospatial abilities, and executive function. The purpose of this study was to determine the effect of language intervention by cognitive approach on language expressive performance in a patient with conduction aphasia. This study used several tasks such as Attention and concentration task, visual memory tasks, memory tasks, categorization, divergent thinking, self-monitoring and evaluate thinking. The effects of treatment were evaluated by periodic probing of both trained and untrained familiar words in three tasks; picture naming, answering to questions and telling stories. The results showed improvements both in trained and untrained words. Therefore, we concluded that expressive language performance of this aphasic patient is amenable to this intervention, and that cognitive therapy approach can be useful.

• ETRI Journal
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• v.46 no.1
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• pp.59-70
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• 2024

We introduce a high-performance named entity recognition (NER) model for written and spoken language. To overcome challenges related to labeled data scarcity and domain shifts, we use transfer learning to leverage our previously developed KorBERT as the base model. We also adopt a meta-pseudo-label method using a teacher/student framework with labeled and unlabeled data. Our model presents two modifications. First, the student model is updated with an average loss from both human- and pseudo-labeled data. Second, the influence of noisy pseudo-labeled data is mitigated by considering feedback scores and updating the teacher model only when below a threshold (0.0005). We achieve the target NER performance in the spoken language domain and improve that in the written language domain by proposing a straightforward rollback method that reverts to the best model based on scarce human-labeled data. Further improvement is achieved by adjusting the label vector weights in the named entity dictionary.

• The Korean Journal of Coaching Psychology
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• v.6 no.2
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• pp.75-92
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• 2022

There are many studies that intrinsic learning motivation and social support play an important role in the study of children and adolescents. However, studies examining the effects of intrinsic learning motivation and social support by measuring the actual academic performance of elementary school students are rare. This study attempted to verify the effect of intrinsic learning motivation on Korean language performance and moderating effect of social support in 5th and 6th graders in elementary school. 122 elementary school students in local county-level areas participated in this study. The Korean language test was conducted about 5 months after intrinsic learning motivation and social support of families and teachers were measured. The results revealed that Korean language performance showed a significant positive correlation with intrinsic learning motivation and social support, and also showed a significant correlation between learning motivation and social support. In the regression analysis with control variables, it was found that intrinsic learning motivation had a significant effect on Korean language performance. The moderating effect of social support was analyzed by dividing it into family support and teacher support. The interaction effect of learning motivation and social support was significant only in teacher support, not in family support. In specific, when teacher support was high, Korean language performance was high regardless of the student's learning motivation level, but when teacher support was low, the student's learning motivation mattered in the performance. Based on the results of this study, implications and limitations were discussed.

• Phonetics and Speech Sciences
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• v.3 no.4
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• pp.95-102
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• 2011

The purpose of this study was to identify the characteristics of the phonological discrimination ability and phonological working memory of 10 typically developing children aged 4, and 10 other children with Specific Language Impairments whose language age is similar. In orders to compare their phonological discrimination ability among phonological awareness, discrimination tasks were conducted at the syllable and phoneme levels. Also, in order to compare their phonological working memory, the subjects repeated nonsense syllables. The research results may be summarized as follows: First, the children with Specific Language Impairments demonstrated a lower performance than the typically developing children in phonological discrimination ability at both syllable and phoneme levels, and the difference between the groups was statistically significant. Second, the children with Specific Language Impairments exhibited a lower phonological working memory performance in all syllables compared with normal children. Although there was no significant difference in 2 and 3 syllables, a significant difference appeared as the length of the syllables became longer from 4 to 6 syllables. It is deemed necessary to conduct research into qualitative and quantitative differences through an formal assessment of the phonological awareness and phonological working memory of children with Specific Language Impairments.

• Journal of Physiology & Pathology in Korean Medicine
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• v.21 no.4
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• pp.1025-1029
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• 2007

It is widely assumed that Intelligence Quotient (IQ) is determined by inherent disposition and environmental factor. IQ is estimated by age-conversion score and stabilized around age 4 and IQ of adult age can be predicted after age 10. Though children with Mental Retardation (MR) are delayed in language development since early infant period, they receive only special education including speech and language therapy, but no special medication. In traditional Korean medicine, the etiology and treatment for developmental delay of language have been handed down for a long time. Some studies on herbs and prescriptions for improving language development have been undertaken recently. We have found several cases of significant elevation of IQ in the children treated with long term medications of Korean herbal medicine for improvement of language. Analyzing these cases, especially performance IQ showed significant change. Therefore we suggest that Korean herbal medicine might improve cognition development in children with MR.

• The Journal of Bigdata
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• v.9 no.1
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• pp.187-196
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• 2024

In this study, we propose a DNN (Deep Neural Network)-based sign language translation model that can significantly reduce training time by compressing sign language coordinates. We compared and analyzed the accuracy and training time of the model with and without sign language coordinate compression. The results of using the proposed model for sign language translation showed that while the accuracy decreased by approximately 5.9% after compressing the sign language video, the training time was reduced by 56.57%, indicating a substantial gain in training efficiency compared to the loss in translation accuracy.

• ETRI Journal
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• v.44 no.5
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• pp.794-804
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• 2022

Transformer models have had a great impact on natural language processing (NLP) in recent years by realizing outstanding and efficient contextualized language models. Recent studies have used transformer-based language models for various NLP tasks, including Persian named entity recognition (NER). However, in complex tasks, for example, NER, it is difficult to determine which contextualized embedding will produce the best representation for the tasks. Considering the lack of comparative studies to investigate the use of different contextualized pretrained models with sequence modeling classifiers, we conducted a comparative study about using different classifiers and embedding models. In this paper, we use different transformer-based language models tuned with different classifiers, and we evaluate these models on the Persian NER task. We perform a comparative analysis to assess the impact of text representation and text classification methods on Persian NER performance. We train and evaluate the models on three different Persian NER datasets, that is, MoNa, Peyma, and Arman. Experimental results demonstrate that XLM-R with a linear layer and conditional random field (CRF) layer exhibited the best performance. This model achieved phrase-based F-measures of 70.04, 86.37, and 79.25 and word-based F scores of 78, 84.02, and 89.73 on the MoNa, Peyma, and Arman datasets, respectively. These results represent state-of-the-art performance on the Persian NER task.

• International Journal of Contents
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• v.12 no.1
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• pp.54-59
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• 2016

The purpose of this paper is to discover how the use of digital applications can affect students' attitudes toward positive classroom participation and performance in learning a foreign language. Participants of this study were 128 students who took a foreign language class at a high school in central Korea. To find out students' perceptions and attitudes toward the effect of using a digital application for their foreign language study, online questionnaire and focus-group interview were conducted. Our research findings revealed that these students could engage in active language learning and experience learning improvement while studying a foreign language with digital applications. The improvement was possible by creating more interactive activities and quizzes. In addition, the digital application provided students immediate feedback. It gave students and teachers various motivations beyond the traditional 'chalk and talk' format of text-only-classes. This study provides an overview of the usefulness of digital application. In addition, it provides understanding for students' perceptions and involvement using digital application in a foreign language classroom.

• Korean Journal of English Language and Linguistics
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• v.3 no.4
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• pp.571-588
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• 2003

The purpose of this study is to investigate into the various ways that the computer technology is used for language testing. Three uses of computer technology are mentioned: 1) computer-adaptive language testing and computer-based language testing, 2) the scoring of performance-based language assessment, and 3) the development and use of psychometric tools for analyzing the scoring results. Although the various uses of computer technology could provide expanded possibilities for language testing development, the developers should be reminded that they are currently subject to indepth research which could support their validity. In this regard, the advantages and limitations of some uses of computer technology for language testing are discussed.