• 한국노년학
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• v.38 no.1
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• pp.1-14
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• 2018

Everyday hearing handicap caused by presbycusis ultimately reduces quality of life in older adults. The aim of this study was to explore effects of cognitive impairment on self-reported hearing handicap in older adults with early-stage presbycusis. We compared K-HHIE scores between 40 elderly subjects with mild cognitive impairment (MCI) and age- and hearing-threshold matched 40 cognitively normal elderly (CNE) subjects. The results are as follows: 1) The MCI group scored significantly higher than the CNE group on the social/situational and emotional sections, and in total. 2) The MCI group scored significantly higher than the CNE group on all four subscales, and the most significant group difference was on the first subscale relating to interpersonal relationships and social handicaps. 3) Both groups scored highest on the item 8 (problems hearing whispering sounds) and item 15 (problems hearing TV or radio sounds). Besides those two items, the MCI group also scored high on the item 21 (problems hearing in a restaurant), item 6 (problems hearing when attending a party), item 3 (avoiding groups of people), and item 20 (personal or social restrictions). Our findings suggest that, among older adults with early-stage presbycusis, older adults with cognitive impairment tend to report greater everyday hearing handicap than their peers with normal cognitive function. Especially, they show significant problems hearing in background noise or multi-talker situations, which cause social restrictions and social/emotional loneliness.

• Journal of the Korea Convergence Society
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• v.10 no.3
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• pp.167-176
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• 2019

The conversational agent, which is at the forefront of the 4th industry, aims to personalize the user-centered focus in the future and holds an important position to have a hub that can be connected to various IoT devices. It is a challenge for interactive agents to recognize the user's emotions and provide the correct interaction to personalization. The study first I looked at emotional definitions and scientific and engineering approaches. Then I recognized through social perspectives what social function and what factors emotions have and how they can be used to understand emotions. Based on this, I explored how users can be discovered emotional social factors in communication. This research has shown that social factors can be found in the user's speech, which can be linked to the social meaning of emotions. Finally, I propose a model to discover social factors in user communication. I hope that this will help designer and researcher to study user-centered design and interaction in designing interactive agents.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.7 no.1
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• pp.3-13
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• 1996

All human being can not exist by oneself That is, all human being depend on intimate attachment for their survival. Physical and psychological powers are prerequisites fir one's survival and these serve important functions hi interpersonal relationships. There are two kinds of powers. One is positive power which helps one survive effectively. Another one is negative power which disturbs one's effective survival. In this paper, the author reviewed the precept of 'trust' which is described in 'Bible' and oriental classical books such as 'The Analects of Confuicus' and 'Tao Te Ching' etc. and tried to integrate this precept with the importance in everyday life, 'How to communicate' is closely related to 'trust' and one's speech is closely related to one's thinking or emotion. Thus in order to keep trustful communication, one has to introspect oneself to understand one's own emotional reaction.

• The Journal of Korea Assosiation for Disability and Oral Health
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• v.7 no.1
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• pp.38-43
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• 2011

Treatment of the mandibular fracture consists of reduction and fixation. Primary wire & Arch bar are perhaps the ideal method for intermaxillary fixation. But, daily feeding, swallowing, speech, and in some instances, respiration is difficult to maintain during the period of intermaxillary fixation, owing to muscle weakness, emotional disorder and poor oral hygiene in a position of the long-term bed disabled patient with multiple injuries. Therefore, Intermaxillary fixation is not applied in the disabled bed patient, the alternative methods must be obtained. In the case of the mandibular fracture, because of the absence of weight bearing, osseous union may eventually occur even without immobilization if the patient is maintained without wound infection on a controlled soft diet. For the purpose of the prevention of the wound infection, the establishment of an drainage on the oral lacerated wound is necessary for the removal of the hematoma & seroma in the fracture site. This is the report of a case that was managed conservatively without the intermaxillary fixation in the long-term disabled bed patient with a mandibular compound fracture.

• Therapeutic Science for Rehabilitation
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• v.9 no.4
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• pp.21-31
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• 2020

Objective : Reminiscence program is a method to restore psychological stability for the elderly having dementia, and at the same time it makes the aged with dementia express themselves correctly by helping them to recollect their past life memories. The purpose of this study was to investigate the effects on communication ability in applying the reminiscence program to elderly patients with Alzheimer's dementia. Methods : The subject were 4 patients whose Alzheimer's dementia of moderate. This experiment was designed with pre-stage, treatment-stage, post-stage. The reminiscence therapy was compose of reminiscence activities of their live; in their childhood, adolescence, adulthood, and senescence. The therapy was delivered 30 times for 15 weeks. Results : The result of the study were as follows. First, after reminiscence therapy, recognition ability was improved. Second, after reminiscence therapy, emotional side was improved. Third, after reminiscence therapy, communication ability was improved. Conclusion : In this study, the reminiscence therapy had a positive effect on the improvement of communication skills among the elderly with Alzheimer's dementia. Based on the reminiscence therapy, it is thought to be very helpful in improving the communication ability of the elderly with dementia in the future.

• The Journal of the Korea Contents Association
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• v.20 no.1
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• pp.573-580
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• 2020

The purpose of this study was to explore and to suggest the effective teaching methods for university students to improve their speaking abilities through peer assessment-feedback and self assessment-feedback based presentation and debate class. The objects and content of the study were the students who took a class "Reading and Communication" of H university, and here examine closely the speaking activities and their effects during the integrated activities of 'reading, speaking and writing'. In speaking education peer and self assessment feedback is to form an emotional consensus among the students and encourage active participation, and enable self-discovery and communication learning to students. As a result of the study, it was found that the variety speaking practice had a very positive effect on the attitude of speaking and the psychological aspect, and it was confirmed that the evaluation and feedback activities had a meaningful learning effect on the students. Effective speech education and guidance measures should be continuously studied and developed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.6C
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• pp.505-511
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• 2005

Autonomic machines interacting with human should have capability to perceive the states of emotion and attitude through implicit messages for obtaining voluntary cooperation from their clients. Voice is the easiest and most natural way to exchange human messages. The automatic systems capable to understanding the states of emotion and attitude have utilized features based on pitch and energy of uttered sentences. Performance of the existing emotion recognition systems can be further improved withthe support of linguistic knowledge that specific tonal section in a sentence is related with the states of emotion and attitude. In this paper, we attempt to improve recognition rate of emotion by adopting such linguistic knowledge for Korean ending boundary tones into anautomatic system implemented using pitch-related features and multilayer perceptrons. From the results of an experiment over a Korean emotional speech database, the improvement of $4\%$ is confirmed.

• Journal of Industrial Convergence
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• v.19 no.6
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• pp.177-186
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• 2021

This review aims to propose a model that can reinterpret the abnormal and functional connections between cognitive processes and emotional regulations based on the neurocognitive networks for a comprehensive understanding of pathologic processes and treatment approach of depression and anxiety disorder. Through the processes of rebuilding the network model for depression and anxiety disorder, it was confirmed that depression can be said to be 'over-immersion in self-referencing' due to hyper-activation of default mode network (DMN), and anxiety disorders to be 'disconnection with self-referencing' due to hypo-activation of DMN. The attempts to link up between abnormal activation and pathological function of DMN which is thought to be involved in self-referential processing associated with self-consciousness and projection among neurocognitive networks may be another starting point that can afford to be suggestive in integrated interpretation and therapeutic approach to depression and anxiety disorder.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.4
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• pp.9-14
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• 2024

This study developed a voice recognition chatbot system to address depression and loneliness among the elderly in an aging society. The system utilizes the Whisper model, GPT 2.5, and XTTS2 to provide high-performance voice recognition, natural language processing, and text-to-speech conversion. Users can express their emotions and states and receive appropriate responses, with voice recognition functionality using familiar voices for comfort and reassurance. The UX/UI design considers the cognitive responses, visual impairments, and physical limitations of the smart senior generation, using high contrast colors and readable fonts for enhanced usability. This research is expected to improve the quality of life for the elderly through voice-based interfaces.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.69-92
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• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.