• The Journal of the Acoustical Society of Korea
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• v.41 no.1
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• pp.52-57
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• 2022

Speech consists of the sum of complex sine-waves. This study investigated the perception of electrical hearing by applying the sinusoidal model to cochlear implant simulation. Fourteen adults with normal hearing participated in this study. The sentence recognition tests were implemented using the sentence lists processed by the sinusoidal model which extracts 2, 4, 6, 8 sine-wave components and sentence lists processed by the same sinusoidal model along with cochlear implant simulation (8 channel vocoders). The results showed lower speech recognition for the sentence lists processed by the sinusoidal model and cochlear implant simulation compared to those by the sinusoidal model alone. Notably, the lower the number of sine-wave components (2), the larger the difference was. This study provides the perceptual pattern of sine-wave speech for electrical hearing by cochlear implant listeners, and basic data for development of speech processing algorithms in cochlear implants.

• The Journal of the Acoustical Society of Korea
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• v.32 no.5
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• pp.430-437
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• 2013

The present study examined whether sentence perception scores were changed under various conditions of time alteration (compression and/or expansion) and selective word stress in normal hearing listeners. Twenty young normal hearing adults (ten males) were participated. As stimuli, Korean standard-sentence list for adults (KS-SL-A) modified to semantically anomalous sentences was newly recorded by a female speaker. Seven different time-altered conditions (e.g., ${\pm}60%$, ${\pm}40%$, ${\pm}20%$, 0 %) were controlled. To see the effect of selective word stress (i.e., the emphasis of specific syllables in the sentence), all subjects were tested twice 2 weeks apart. The results showed 1) there was significantly different sentence perception scores among the different time-altered conditions, yet only in the 60 % compression condition; 2) there was no significant difference of the sentence perception scores in the effect of stress; however, there was a positive effect of the selective word stress in the sentences consisting of 6 ~ 7 syllables at the 40 % compression condition; 3) there was no significant gender difference. The pattern of results suggests that the combination of time compression and selective word stress is more effective to understand speech, instead of only using time expansion condition. However, further studies should be needed for standardization.

• 대한상한금궤의학회지
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• v.10 no.1
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• pp.81-94
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• 2018

Objective : The objective of this study is to define the clinical meaning of Shanghanlun sentence by applying Shanghanlun disease pattern identification diagnostic system. Methods : 2 clinical cases, which were treated by Oreong-san according to Shanghanlun provisions dualized with Je-Gang(提綱) and Jo-Moon(條文), were analyzed. Results : According to the results of analysis of 2 cases, the patients' diseases were improved. The pain was decreased, and general weakness and anorexia were improved in 2 cases. Conclusions : These results suggests that the medicines from Shanghanlun are clinically effective when Shanghanlun is interpreted considering the origins of Chinese characters in the text, and Shanghanlun disease pattern identification diagnostic system is applied.

• Science of Emotion and Sensibility
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• v.17 no.1
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• pp.71-78
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• 2014

We propose the sentiment pattern as a novel sentiment feature for more accurate text sentiment analysis, and introduce the rating inference of movie reviews using it. The text sentiment analysis is a task that recognizes and classifies sentiment of text whether it is positive or negative. For that purpose, the sentiment feature is used, which includes sentiment words and phrase pattern that have specific sentiment like positive or negative. The previous researches for the sentiment analysis, however, have a limit to understand accurately total sentiment of either a sentence or text because they consider the sentiment of sentiment words and phrase patterns independently. Therefore, we propose the sentiment pattern that is defined by arranging semantically all sentiment in a sentence, and use them as a new sentiment feature for the rating inference that is one of the detail subjects of the sentiment analysis. In order to verify the effect of proposed sentiment pattern, we conducted experiments of rating inference. Ratings of test reviews is inferred by using a probabilistic method with sentiment features including sentiment patterns extracted from training reviews. As a result, it is shown that the result of rating inference with sentiment patterns are more accurate than that without sentiment patterns.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.498-500
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• 2003

인터넷의 급속한 팽창으로 인해 가을 정보의 양이 폭발적으로 증가하고 있다. 웹 사용자에게 이용 가치가 없는 정보 범람(information overflow)안이 발생한다면 효율적인 정보검색이 되지 못하므로 사용자가 원하는 정보만을 얻을 수 있다면 시간과 미숙한 정보의 검색을 방지 할 수 있다. 본 논문에서는 한국어 질의 생성과 관련하여 웹 사용자의 편의성과 효율성을 고려한 한국어 질의 처리 방법론과 개인형 메타 검색 모델을 제안하고자 한다. 한국어 질의를 기본으로 하여 한국어 문장 패턴 및 개인 정보 평가 구성 요소를 이용한 방법론과 모델을 제안하고자 한다.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.2
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• pp.205-212
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• 2013

The previous chatting systems have generally used methods based on lexical agreement between users' input sentences and target sentences in a database. However, these methods often raise well-known lexical disagreement problems. To resolve some of lexical disagreement problems, we propose a three-step sentence searching method that is sequentially applied when the previous step is failed. The first step is to compare common keyword sequences between users' inputs and target sentences in the lexical level. The second step is to compare sentence types and semantic markers between users' input and target sentences in the semantic level. The last step is to match users's inputs against predefined lexico-syntactic patterns. In the experiments, the proposed method showed better response precision and user satisfaction rate than simple keyword matching methods.

• Journal of the Korean School Mathematics Society
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• v.15 no.4
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• pp.699-718
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• 2012

The purpose of mathematics eduction is to develop the ability of thinking mathematically. It informs method to solve problem through mathematical thinking that teach mathematical ability. Errors in the problem solving can be thought as those in the mathematical thinking. Therefore analysis and classification of mathematics errors is important to teach mathematics. This study researches the preceding studies on mathematics errors and presents the characteristic of them with analyzed models. The results achieved by analysis of the process of problem solving are as follows : ▸ Students feel much harder to solve words problems rather than multiple-choice problems. ▸ The length of sentence make some differences of understanding of the words problems. Students easy to understand short sentence problems than long sentence problems. ▸ If students feel difficulties on the pre-learned mathematical content, they feel the same difficulties on the words problems based on the pre-learned mathematics content.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.337-340
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• 2004

The exactly reproduced prosody of a TTS system is one of the key factors that affect the naturalness of synthesized speech. In general, rules about prosody had been gathered either from linguistic knowledge or by analyzing the prosodic information from natural speech. But these could not be perfect and some of them could be incorrect. So we proposed artificial neural network(ANN)s that can be trained to team the prosody of natural speech and generate it. In learning phase, let ANNs learn the pitch and energy contour of center phoneme by applying a string of phonemes in a sentence to ANNs and comparing the output pattern with target pattern and making adjustment in weighting values to get the least mean square error between them. In test phase, the estimation rates were computed. We saw that ANNs could generate the prosody of a sentence.

• Journal of KIISE
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• v.45 no.2
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• pp.157-164
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• 2018

Due to the revolutionary advances in deep learning, performance of pattern recognition has increased significantly in many applications like speech recognition and image recognition, and some systems outperform human-level intelligence in specific domains. Unlike pattern recognition, in this paper, we focus on generating Korean sentences based on a few Korean sentences. We apply variational recurrent auto-encoder (VRAE) and modify the model considering some characteristics of Korean sentences. To reduce the number of words in the model, we apply a word spacing model. Also, there are many Korean sentences which have the same meaning but different word order, even without subjects or objects; therefore we change the unidirectional encoder of VRAE into a bidirectional encoder. In addition, we apply an interpolation method on the encoded vectors from the given sentences, so that we can generate new sentences which are similar to the given sentences. In experiments, we confirm that our proposed method generates better sentences which are semantically more similar to the given sentences.

• Annual Conference on Human and Language Technology
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• 1999.10e
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• pp.105-109
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• 1999

영-한 기계번역 중 변환 단계에서 한국어 문장을 생성하기 위해서는 구구조 변환 후 조사 및 대역어 선택으로 이루어진다. 그러나 하나의 영어 단어는 여러 개의 한국어 의미들을 가지고 있기 때문에 문장에서 사용된 영어의 정확한 의미에 해당하는 한국어 대역어를 선택하는 것은 번역의 질을 높이고 시스템의 성능에 매우 중요한 역할을 한다. 특히 용언 및 체언의 대역어 선택은 문장에서 서로 간의 의미적인 관계를 고려하여야 올바른 대역어를 선택할 수 있다. 기존에는 전자 사전에 용언과 체언간의 연어 정보(collocation information)를 구축하여 대역어 선택의 문제를 해결하려고 하였으나 연어 정보가 사전에 존재하지 않을 때 올바른 대역어를 선택할 수 없었다. 또한 용언과 체언의 관계를 나타내는 조사를 선택하기 위하여 격(case)을 세분화하여 사전을 구축하였으나 격의 분류 및 사전을 구축할 경우 격을 선택하는 어려움이 있었다. 이에 따라 본 논문에서는 문형(sentence pattern)에 의한 방법으로 용언의 대역어 및 용언이 갖는 필수격 체언의 조사와 대역어 선택방법을 제안한다. 문형의 구조적인 정보에는 용언과 체언의 의미적 역할(thematic role)을 하는 조사 및 용언이 갖는 필수격 체언의 의미 자질(semantic feature)을 갖고 있다. 이러한 의미 자질을 wordnet과 한/영 및 영/한 사전을 이용하여 의미 지표(semantic marker)를 갖는 문형 사전을 구축한다. 또한 의미 지표를 갖는 문형 사전을 기반으로 조사 및 대역어 선택 알고리즘을 개발한다.