• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.63-70
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• 2006

In general, a corpus contains lots of linguistic information and is widely used in the field of natural language processing and computational linguistics. The creation of such the corpus, however, is an expensive, labor-intensive and time-consuming work. To alleviate this problem, annotation tools to build corpora with much linguistic information is indispensable. In this paper, we design and implement an annotation tool for establishing a Korean dependency tree-tagged corpus. The most ideal way is to fully automatically create the corpus without annotators' interventions, but as a matter of fact, it is impossible. The proposed tool is semi-automatic like most other annotation tools and is designed to edit errors, which are generated by basic analyzers like part-of-speech tagger and (partial) parser. We also design it to avoid repetitive works while editing the errors and to use it easily and friendly. Using the proposed annotation tool, 10,000 Korean sentences containing over 20 words are annotated with dependency structures. For 2 months, eight annotators have worked every 4 hours a day. We are confident that we can have accurate and consistent annotations as well as reduced labor and time.

• MALSORI
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• no.19_20
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• pp.58-87
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• 1990

According to Government Phonology, at 1 phonological positions save the domain's head must be licensed in order to appear in the syllable structure. A non-nuclear head is licensed by the following nucleus, and the nuclei with phonetic content are licensed through government by the nuclear head of the domain at the level of the nuclear projection. Therefore, in the theory of Government Phonology it is claimed that words always end with a nucleus. With regard to the licensing of empty nuclei, Kaye(1990a) proposes the 'Empty Category Principle' and its sub-theory of 'Projection Government'. Government Phonology claims that a nucleus which dominates a vowel that regularly undergoes elision in certain contexts is underlyingly empty. This underlying empty nucleus is not manifested phonetically when it is properly governed by an unlicensed(i, e, a nucleus filled with a full vowel). It is when proper government fails to apply, that the empty nucleus is phonetically Interpreted. The purpose of this paper is to present a principled account of the process of $[i]{\Leftrightarrow}{\emptyset}$ alternation in Korean. Following Kaye's proposal, we assume that [i] of Korean is underlyingly empty. This position is pronounced as [i] if it is unlicensed, and is not phonetically realized if is licensed. Empty nuclei ape devided into two categories: domain-internal and domain-final. Firstly, we consider the question why Korean has little word ending with [i]. As for this, ECP states that domain-final empty nuclei are not pronounced if the language licenses domain-final empty nuclei. Whether a final empty nucleus may occur in the structure is parametric variation. This property is seen from the fact that words may appear to end in consonants in this language. Since Korean abounds with words ending in a consonant, it licenses domain-final empty nuclei. Therefore, it is quite natural that Korean has little word ending with [i]. Secondly, word-internal empty nuclei of Korean respect proper government and inter-onset government. That is, an empty nucleus in word-internal position will be pronounced with the vowel [i] if either proper government or inter-onset government fail to apply. Inter-onset government refers to the government established between two onsets across an empty nucleus. Thirdly, we consider words ending with [i], which seems to be exceptional to the final licensing. Host of them are. either mono-syllabic verbs(for instance, [s'i-] 'to write') or derived adjectives ending with [p'i] (for instance, [kip'i-] 'be happy'). As for the former, the 'inaccessibility for proper government' is applied because the empty nucleus appears in the first syllable. In latter case, domain-final empty nuclei are pronounced as [i] because of government-licensing. That is, final empty nucleus is pronounced to license the preceding onset dominating negatively charmed segments which empty nucleus of Korean cannot license.

• Clinical and Experimental Pediatrics
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• v.53 no.4
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• pp.579-584
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• 2010

Purpose : The number of the repatriated Korean students who had overseas study at early ages is increasing. They received foreign education, they can speak international languages, but they have many difficulties in articulation and intonation of the Korean language. This study aims to measure closure and aspiration duration, length of consonants, length of subsequent vowels, and ratio of consonants against subsequent vowels in vowel-consonant-vowel (VCV) syllables. Methods : This study compares the acoustic and phonetic characteristics of repatriated and native students, the ratio of articulation error of Korean plosives, the closure and aspiration duration, and the ratio of the aspiration duration against the closure duration. Results : The ratio of articulation error of Korean plosives between repatriated and native students is 19% and 2%, respectively. The closure duration was significantly longer in repatriated students than in native students. The aspiration duration was significantly longer in repatriated students than in native students. No difference was found in the ratio of aspiration duration against closure duration between the native and repatriated students. Conclusion : This study can be a good reference for estimating the phonetic difficulties of Korean elementary students who had overseas study at early ages.

• Journal of the HCI Society of Korea
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• v.7 no.2
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• pp.35-42
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• 2012

The purpose of this study was to evaluate the usability of the tablet PC-based Korean high-tech AAC(Augmentative Alternative Communication System) software. In order to develop an AAC software which is appropriate to Korean cultural/linguistic contexts and communication needs of the users, we examined the necessity and ease of use for the communication functions that are required in native Korean communication, such as polite expressions, tense expressions, negative expressions, subject-verb auto-matching, and automatic sentence generation functions, using a scenario-based user testing. We also investigated the users' needs, preferences, and satisfaction for the tablet PC-based Korean high tech AAC using a semi-structured and open questionnaires. The participants of this study were 9 special education teachers, 6 speech therapists, and 6 parents whose children had communication disabilities. The results of the usability testing of the tablet PC-based Korean high-tech AAC software presented positive responses in general, by indicating overall scores of above 4 out of 5 except in tense and negative expressions. The necessity and ease of use in the tense and negative expressions were evaluated relatively low, and it might be related to the inconsistent interface with the polite expressions. In terms of the user interface(UI), there were users' needs for clear visual feedback in the symbol selection and display, consistent interface for all functions, more natural subject-verb auto-matching, and spacing in the text within symbols. The results of the usability testing and users' feedback might serve as a guideline to compensate and improve the function and UI of the existing AAC software.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.7
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• pp.221-228
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• 2020

Part-of-Speech (POS) tagged corpus is a collection of electronic text in which each word is annotated with a tag as the corresponding POS and is widely used for various training data for natural language processing. The training data generally assumes that there are no errors, but in reality they include various types of errors, which cause performance degradation of systems trained using the data. To alleviate this problem, we propose a novel method for detecting errors in the existing POS tagged corpus using the classifier of XGBoost and cross-validation as evaluation techniques. We first train a classifier of a POS tagger using the POS-tagged corpus with some errors and then detect errors from the POS-tagged corpus using cross-validation, but the classifier cannot detect errors because there is no training data for detecting POS tagged errors. We thus detect errors by comparing the outputs (probabilities of POS) of the classifier, adjusting hyperparameters. The hyperparameters is estimated by a small scale error-tagged corpus, in which text is sampled from a POS-tagged corpus and which is marked up POS errors by experts. In this paper, we use recall and precision as evaluation metrics which are widely used in information retrieval. We have shown that the proposed method is valid by comparing two distributions of the sample (the error-tagged corpus) and the population (the POS-tagged corpus) because all detected errors cannot be checked. In the near future, we will apply the proposed method to a dependency tree-tagged corpus and a semantic role tagged corpus.

• 재활복지
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• v.22 no.4
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• pp.103-121
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• 2018

For knowing the effects of aging on conversational skills in daily communication, this paper studied for the conversational turn-taking skills, working memory and naming ability on healthy elderly adults over 65 ages. 85 elderly adults participated in this study, which divided into four groups by ages. Speech samples were collected in natural conversation. Memorization of numbers, mental calculation, repetition of words were administered for working memory test. K-BNT was used for the naming ability. One-way ANOVA analysis was used for the comparison of conversational turn-taking skills among four groups. We analyzed the correlation between conversational skills, working memory and naming ability. The results were as follows: first, there were a significant difference in conversational turn-taking skills by age, but not by gender. There was a significant difference in 'Turn-Taking Frequency' and 'Total Utterance Frequency' among four groups. The same results were shown in the scores of females within three groups(exclude groups over 85D)(p<.01). Second, there was a significant correlation between 'rates of maintenance' and 'naming ability'. In addition, it was found that the naming test predicted 'rates of maintenance' skills. The results of this study suggest that word-retrieval ability will be helpful to enhance functional communication skills in aging old adults.

• Journal of Korean Classical Literature and Education
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• no.32
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• pp.29-61
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• 2016

A joke (才談, 재담) is "the most interesting and witty language unit" in our speech. However, the search of a joke is still starting. Although joke are related to the witty and interesting talks, stories, songs and plays, the actual object of a joke is only the witty and interesting talk. A joke is witty talk that is interesting or laughter-inducing. Many Jokes can be found in the traditional Korean funny performing arts (演戱, 연희). This is because these art forms are performed in open yards, which necessitated amusing the audience, amusement, in its turn, required jokes. Jokes in the traditional funny performing arts can generally be classified as follows: 1) Jokes related to a situation: These include right words at a given situation, exaggerating words, diminishing words, deviancy words, and cause-effect words. 2) Jokes related to discourse: These include enumerating words, amplificatory words, contrasting words, fluently lying words, undeniable words, purposely unknowing words, and deliberately incorrect words. 3) Jokes related to vocabulary: These include synonym, similar words, changed word-ordering words, and incorrect words. 4) Jokes related to pronunciation: These include homonyms, and anti-homonyms. Although there may be other jokes, those presented above are typical ones. A joke is "the result that human being can achieve when he/she has overcome natural and social difficulties and is left with only a free and creative spirit." Jokes are necessary in all ages and everywhere. Today, more varied and high-level jokes can be created by developing the diversity of jokes in traditional funny performing arts. Also, I expect new sorts of jokes, because a joke always demands a creative spirit.

• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.495-505
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• 2019

Typical algorithms of deep learning include CNN(Convolutional Neural Networks), which are mainly used for image recognition, and RNN(Recurrent Neural Networks), which are used mainly for speech recognition and natural language processing. Among them, CNN is able to learn from filters that generate feature maps with algorithms that automatically learn features from data, making it mainstream with excellent performance in image recognition. Since then, various algorithms such as R-CNN and others have appeared in object detection to improve performance of CNN, and algorithms such as YOLO(You Only Look Once) and SSD(Single Shot Multi-box Detector) have been proposed recently. However, since these deep learning-based detection algorithms determine the success of the detection in the still images, stable object tracking and detection in the video requires separate tracking capabilities. Therefore, this paper proposes a method of combining Kalman filters into deep learning-based detection networks for improved object tracking and detection performance in the video. The detection network used YOLO v2, which is capable of real-time processing, and the proposed method resulted in 7.7% IoU performance improvement over the existing YOLO v2 network and 20 fps processing speed in FHD images.

• The Journal of Korean Philosophical History
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• no.50
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• pp.171-200
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• 2016

The full-scaled study of Joseon conducted by Japan in the 1910s was part of its colonial policy, while the native Joseon studies against it contained political aspiration to recover the national rights and independence. Accordingly, the conceptual meaning of 'Joseon' varied according to its subject of speech. The establishment of modern nation-state failed along with the extinction of Korean Empire, but 'Joseon' was newly discovered within national ideology. It became a historical concept in which the experience of the past and the expectation toward the future could be united. The so-called 'Joseon Studies' was only limited to intellectuals in the academic circle, but 'Joseon' embraced the articulations from more various social agents. Furthermore, it is only natural that 'Joseon Studies' should be interpreted within the historical semantics of 'Joseon', considering the connection between concept and discourse. In his The History of Joseon Civilization, An Hwak encompassed the history from the times of ancient mythology to the contemporary times under the banner of 'Joseon'. Opposing Japanese distortion of history carried out in the name of historical positivism, he idealized Joseon history as comparable to that of the Western democracy. He extended the study of 'Joseon' into culture at large, foreshadowing a kind of Joseon philosophy. In his An Overview of Joseon Philosophical Ideas, the first description of 'Joseon philosophy' as an independent field, he proposed philosophy as one of three sources of pride in Joseon and asserted its uniqueness and originality compared to the West. It was an attempt to grasp the peculiarity of Joseon ideas from a perspective of the history of universal human civilization. He considered 'Jong'(倧) as an ideological foundation held from the ancient to the modern times, and the acceptance of Buddhism and Confucianism as beneficial to 'Joseon philosophy'. The birth of 'Joseon philosophy', the modern transformation of the traditional knowledge system, was an intellectual experiment to apply traditional knowledge to the modern disciplinary classification system.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1137-1144
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• 2022

In this study, an artificial intelligence(AI) was developed to help with facial expression practice in order to express emotions. The developed AI used multimodal inputs consisting of sentences and facial images for deep neural networks (DNNs). The DNNs calculated similarities between the emotions predicted by the sentences and the emotions predicted by facial images. The user practiced facial expressions based on the situation given by sentences, and the AI provided the user with numerical feedback based on the similarity between the emotion predicted by sentence and the emotion predicted by facial expression. ResNet34 structure was trained on FER2013 public data to predict emotions from facial images. To predict emotions in sentences, KoBERT model was trained in transfer learning manner using the conversational speech dataset for emotion classification opened to the public by AIHub. The DNN that predicts emotions from the facial images demonstrated 65% accuracy, which is comparable to human emotional classification ability. The DNN that predicts emotions from the sentences achieved 90% accuracy. The performance of the developed AI was evaluated through experiments with changing facial expressions in which an ordinary person was participated.