• Journal of Sasang Constitutional Medicine
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• v.33 no.4
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• pp.23-31
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• 2021

Objective The case report showed that sudden hearing loss and tinnitus after trigeminal schwannoma surgery were improved with Yeoldahansotang-gamibang. Method The patient was diagnosed with Taeeumin interior heat (Ganyeol) disease based on the original symptoms of Taeeumin. He was treated with herbal medicine and acupuncture treatment. Puretone audiometry (PTA), speech audiometry, tinnitus handicap inventory (THI) and the original symptoms were investigated before and after the treatment. Results Right side PTA score was significantly reduced, speech audiometry was improved in speech reception threshold (SRT), word recognition score (WRS) and most comfortable level (MCL) and THI score decreased from 40 to 0, which showed normalizing hearing function. And the patient revealed improvements in sleeping, digestion, stooling, perspiration and facial sensation after treatment. Conclusion This study suggests that Yeoldahansotang-gamibang is effective on sudden hearing loss and tinnitus after surgery by correcting the imbalanced energy of Taeeumin.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.145-154
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• 2022

Automatic Target Recognition (ATR) technology is emerging as a core technology of Future Combat Systems (FCS). Conventional ATR is performed based on IMINT (image information) collected from the SAR sensor, and various image-based deep learning models are used. However, with the development of IT and sensing technology, even though data/information related to ATR is expanding to HUMINT (human information) and SIGINT (signal information), ATR still contains image oriented IMINT data only is being used. In complex and diversified battlefield situations, it is difficult to guarantee high-level ATR accuracy and generalization performance with image data alone. Therefore, we propose a knowledge graph-based ATR method that can utilize image and text data simultaneously in this paper. The main idea of the knowledge graph and deep model-based ATR method is to convert the ATR image and text into graphs according to the characteristics of each data, align it to the knowledge graph, and connect the heterogeneous ATR data through the knowledge graph. In order to convert the ATR image into a graph, an object-tag graph consisting of object tags as nodes is generated from the image by using the pre-trained image object recognition model and the vocabulary of the knowledge graph. On the other hand, the ATR text uses the pre-trained language model, TF-IDF, co-occurrence word graph, and the vocabulary of knowledge graph to generate a word graph composed of nodes with key vocabulary for the ATR. The generated two types of graphs are connected to the knowledge graph using the entity alignment model for improvement of the ATR performance from images and texts. To prove the superiority of the proposed method, 227 documents from web documents and 61,714 RDF triples from dbpedia were collected, and comparison experiments were performed on precision, recall, and f1-score in a perspective of the entity alignment..

• International Journal of Contents
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• v.17 no.4
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• pp.1-15
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• 2021

Named entity recognition (NER) is a crucial task for NLP, which aims to extract information from texts. To build NER systems, deep learning (DL) models are learned with dictionary features by mapping each word in the dataset to dictionary features and generating a unique index. However, this technique might generate noisy labels, which pose significant challenges for the NER task. In this paper, we proposed DL-dictionary features, and evaluated them on two datasets, including the OntoNotes 5.0 dataset and our new infectious disease outbreak dataset named GFID. We used (1) a Bidirectional Long Short-Term Memory (BiLSTM) character and (2) pre-trained embedding to concatenate with (3) our proposed features, named the Convolutional Neural Network (CNN), BiLSTM, and self-attention dictionaries, respectively. The combined features (1-3) were fed through BiLSTM - Conditional Random Field (CRF) to predict named entity classes as outputs. We compared these outputs with other predictions of the BiLSTM character, pre-trained embedding, and dictionary features from previous research, which used the exact matching and partial matching dictionary technique. The findings showed that the model employing our dictionary features outperformed other models that used existing dictionary features. We also computed the F1 score with the GFID dataset to apply this technique to extract medical or healthcare information.

• Annual Conference on Human and Language Technology
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• 2017.10a
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• pp.147-150
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• 2017

Deep learning의 개발에 따라 개체명 인식에도 neural network가 적용된 연구가 활발히 일어나고 있다. 영어권 개체명 인식에서는 F1 score 90%을 웃도는 성능을 내는 연구들이 나오고 있다. 하지만 한국어는 영어와 언어적 특질이 많이 달라 이를 그대로 적용시키는 데는 어려움이 있어 영어권 개체명 인식기에 비해 비교적 낮은 성능을 보인다. 본 논문에서는 "하다" 접사의 동사형이 보존된 워드 임베딩을 사용하고 한국어 개체명의 특징을 담은 one-hot 벡터를 추가하여 한국어의 특질에 보다 적합한 데이터를 deep learning 기술에 적용하였다.

• 한국어정보학회:학술대회논문집
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• 2017.10a
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• pp.147-150
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• 2017

Deep learning의 개발에 따라 개체명 인식에도 neural network가 적용된 연구가 활발히 일어나고 있다. 영어권 개체명 인식에서는 F1 score 90%을 웃도는 성능을 내는 연구들이 나오고 있다. 하지만 한국어는 영어와 언어적 특질이 많이 달라 이를 그대로 적용시키는 데는 어려움이 있어 영어권 개체명 인식기에 비해 비교적 낮은 성능을 보인다. 본 논문에서는 "하다" 접사의 동사형이 보존된 워드 임베딩을 사용하고 한국어 개체명의 특징을 담은 one-hot 벡터를 추가하여 한국어의 특질에 보다 적합한 데이터를 deep learning 기술에 적용하였다.

• The Journal of the Acoustical Society of Korea
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• v.18 no.3
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• pp.3-9
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• 1999

This paper presents the study on the rejection capability based on anti-phone modeling for vocabulary independent speech recognition system. The rejection system detects and rejects out-of-vocabulary words which were not included in candidate words which are defined while the speech recognizer is made. The rejection system can be classified into two categories by their implementation methods, keyword spotting method and utterance verification method. The keyword spotting method uses an extra filler model as a candidate word as well as keyword models. The utterance verification method uses the anti-models for each phoneme for the calculation of confidence score after it has constructed the anti-models for all phonemes. We implemented an utterance verification algorithm which can be used for vocabulary independent speech recognizer. We also compared three kinds of means for the calculation of confidence score, and found out that the geometric mean had shown the best result. For the normalization of confidence score, usually Sigmoid function is used. On using it, we compared the effect of the weight constant for Sigmoid function and determined the optimal value. And we compared the effects of the size of cohort set, the results showed that the larger set gave the better results. And finally we found out optimal confidence score threshold value. In case of using the threshold value, the overall recognition rate including rejection errors was about 76%. This results are going to be adapted for stock information system based on speech recognizer which is currently provided as an experimental service by Korea Telecom.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.430-440
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• 2021

The purpose of this study was to analyze the degree of depression, cognitive function, communication ability, and the quantitative electroencephalogram (EEG) in elderly individuals with hearing loss and to investigate their inter-relationship. Hearing-impaired elderly participants, aged 60 years or older (37 men and 26 women) who visited the S Hearing Rehabilitation Center in Y City from June 20, 2020, to September 3, 2020, participated voluntarily after a recruitment announcement.The participants' overall characteristics, depression, and cognitive functions were evaluated with a structured questionnaire. The Word Recognition Score (WRS) was evaluated with an audiometer using the Korean Standard Monosyllabic Word Lists for Adults (KS-MWL-A). The quantitative EEG was measured with dry electrodes using a 2-channel EEG on the frontal lobes Fp1 and Fp2. The results are summarized as follows: Communication ability showed a positive correlation with the left-right symmetry of the frontal lobes (**p<.01) and a negative correlation with right-brain mental distraction and stress (*p<.05). In the difference WRS test for each group, the left-right symmetry of the frontal lobes (**p<.01) showed the greatest correlation with communication ability. Our results suggest that the left-right symmetry of the frontal lobes can be a biomarker indicative of the communication ability of older people with hearing impairments.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.5 no.1
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• pp.41-46
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• 2011

A sensorineural hearing loss(SNHL) occurs when the cochlea in the inner has functional problem. The region in the cochlea with no(or very few) functioning inner hair cells or neurons called 'dead regions'. Amplification using hearing aid over a frequency range corresponding to a dead region may not a beneficial. In this paper, we compared speech recognition with different location of dead region and gain and searched effective gain for hearing aid with dead region. In order to experiment, eight people who has normal hearing ware tested, and we used white noise and babble noise(SNR=0 dB). we divided by three conditions, low, mid and high frequency dead region. In addition, the gains in dead region ware 14.5 dB, 11.5dB and 6 dB gain. There ware different results by location of dead region. The result of WRS and preference in mid-frequency dead region and high-frequency dead region ware higher than them in low-frequency dead region. When we compared as gains, the score of WRS with lower gain was higher than 14.5 dB gain, and the preference was lower as higher gain.

• The Journal of the Acoustical Society of Korea
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• v.31 no.5
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• pp.298-308
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• 2012

This study was designed to examine the phoneme recognition errors of hearing-impaired (HI) listeners on a consonant-by-consonant basis, to show (1) how each HI ear perceives individual consonants differently and (2) how standard clinical measurements (i.e., using a tone and word) fail to predict these differences. Sixteen English consonant-vowel (CV) syllables of six signal-to-noise ratios in speech-weighted noise were presented at the most comfortable level for ears with mild-to-moderate sensorineural hearing loss. The findings were as follows: (1) individual HI listeners with a symmetrical pure-tone threshold showed different consonant-loss profiles (CLPs) (i.e., over a set of the 16 English consonants, the likelihood of misperceiving each consonant) in right and left ears. (2) A similar result was found across subjects. Paired ears of different HI individuals with identical pure-tone threshold presented different CLPs in one ear to the other. (3) Paired HI ears having the same averaged consonant score demonstrated completely different CLPs. We conclude that the standard clinical measurements are limited in their ability to predict the extent to which speech perception is degraded in HI ears, and thus they are a necessary, but not a sufficient measurement for HI speech perception. This suggests that the CV measurement would be a useful clinical tool.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.35 no.2
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• pp.82-94
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• 2022

Objectives : The purpose of this study is to report the effect of east-west medical combined treatment of sudden sensorineural hearing loss(SSNHL) through cooperation in a hospital. Methods : We treated three patients diagnosed as SSNHL by combination of herbal medicine, acupuncture, pharmoacupuncture, moxibustion, cupping, laser therapy and conventional medications. We evaluated the results of this treatment with pure tone audiometry, word recognition score(WRS), the changes in distortion product otoacoustic emissions(DPOAE) and visual analogue scale. Results : One of them showed a meaningful improvement in the hearing level of the low frequency region. The others showed 'Complete recovery' in pure tone audiometry and WRS. The subjective symptoms including tinnitus and ear fullness improved in three patients. Conclusion : This study suggests that east-west medical combined treatment is effective on SSNHL patients.