• Proceedings of the KSPS conference
• /
• 2000.07a
• /
• pp.178-178
• /
• 2000

This paper IS concerned with adults' foreign language aquisition and intends to research the relationship between the mother tongue's phonetic system (L1) and the perception of the foreign language (L2), in this paper Polish and Korean. The questions that are to help to define the aforementioned relationship are I) how Polish perceive Korean vowels, 2) how Koreans perceive Polish vowels, and 3) how Koreans perceive Korean vowels pronounced by Poles. In order to identify L2's vowels, the listeners try to fit them into the categories of their own language (L1). On the one hand, vowels that are the same in both languages and those that are articulated where no other vowel is articulated, have the best rate of recognition. For example, /i/ in both languages is a front close vowel and in both languages there are no other front close vowels. Therefore, vowels /i/ (and /a/) have the best rate of recognition in all three experiments. On the other hand, vowels that are unfamiliar to the listeners do not seem to have the worst rate of recognition. The vowels that have the worst rate of recognition are those, that are similar, but not quite the same as those of L1. This research proves that "equivalence classification prevents L2 learners from producing similar L2 phones, but not new L2 phones, authentically" (Flege, 1987). Polish speakers can pronounce unfamiliar L2 vowels "more authentically" than those similar to L1 vowels. However, the difference is not significant and this subject requires further research (different data, more informants).

• The Journal of the Korea institute of electronic communication sciences
• /
• v.15 no.2
• /
• pp.291-298
• /
• 2020

Sign language was designed for the deaf and dumb people to allow them to communicate with others and connect to the society. However, sign language is uncommon to the rest of the society. The unresolved communication barrier had eventually isolated deaf and dumb people from the society. Hence, this study focused on design and implementation of a wearable sign language interpreter. 6 inertial measurement unit (IMU) were placed on back of hand palm and each fingertips to capture hand and finger movements and orientations. Total of 28 proposed word-based American Sign Language were collected during the experiment, while 156 features were extracted from the collected data for classification. With the used of the long short-term memory (LSTM) algorithm, this system achieved up to 99.89% of accuracy. The high accuracy system performance indicated that this proposed system has a great potential to serve the deaf and dumb communities and resolve the communication gap.

• Journal of English Language & Literature
• /
• v.55 no.1
• /
• pp.129-152
• /
• 2009

The paper aims to prove symmetries of the left and right edges of a morphological unit through the analysis of English blends. Blends are the words derived from two existing words by snipping the middle parts out and putting the rest together, such as smog (

• Journal of KIISE:Software and Applications
• /
• v.36 no.1
• /
• pp.82-91
• /
• 2009

Sign language spotting is the task of detecting and recognizing the signs in a signed utterance. The difficulty of sign language spotting is that the occurrences of signs vary in both motion and shape. Moreover, the signs appear within a continuous gesture stream, interspersed with transitional movements between signs in a vocabulary and non-sign patterns(which include out-of-vocabulary signs, epentheses, and other movements that do not correspond to signs). In this paper, a novel method for designing a threshold model in a conditional random field(CRF) model is proposed. The proposed model performs an adaptive threshold for distinguishing between signs in the vocabulary and non-sign patterns. A hand appearance-based sign verification method, a short-sign detector, and a subsign reasoning method are included to further improve sign language spotting accuracy. Experimental results show that the proposed method can detect signs from continuous data with an 88% spotting rate and can recognize signs from isolated data with a 94% recognition rate, versus 74% and 90% respectively for CRFs without a threshold model, short-sign detector, subsign reasoning, and hand appearance-based sign verification.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.44 no.4 s.316
• /
• pp.48-54
• /
• 2007

Hand shape is one of important elements in Korean Sign Language (KSL), which is a communication method for the deaf. To express sign motion in a virtual reality environment based on OpenGL, we need an editor which can insert and modify sign motion data. However, it is very difficult that people, who lack knowledge of sign 1anguage, exactly edit and express hand shape using the existing editors. We also need a program to efficiently construct and store the hand shape data because the number of data is very large in a sign word dictionary. In this paper we developed a KSL hand shape editor to easily construct and edit hand shape by a graphical user interface (GUI), and to store it in a database. Hand shape codes are used in a sign word editor to synthesize sign motion and decreases total amount of KSL data.

• Journal of Korea Multimedia Society
• /
• v.25 no.10
• /
• pp.1535-1545
• /
• 2022

Sign language has completely different meaning depending on the direction of the hand or the change of facial expression even with the same gesture. In this respect, it is crucial to capture the spatial-temporal structure information of each movement. However, sign language translation studies based on Sign2Gloss2Text only convey comprehensive spatial-temporal information about the entire sign language movement. Consequently, detailed information (facial expression, gestures, and etc.) of each movement that is important for sign language translation is not emphasized. Accordingly, in this paper, we propose Spatial-temporal Keypoints Centered Sign2Gloss2Text Translation, named STKC-Sign2 Gloss2Text, to supplement the sequential and semantic information of keypoints which are the core of recognizing and translating sign language. STKC-Sign2Gloss2Text consists of two steps, Spatial Keypoints Embedding, which extracts 121 major keypoints from each image, and Temporal Keypoints Embedding, which emphasizes sequential information using Bi-GRU for extracted keypoints of sign language. The proposed model outperformed all Bilingual Evaluation Understudy(BLEU) scores in Development(DEV) and Testing(TEST) than Sign2Gloss2Text as the baseline, and in particular, it proved the effectiveness of the proposed methodology by achieving 23.19, an improvement of 1.87 based on TEST BLEU-4.

• Electronics and Telecommunications Trends
• /
• v.38 no.6
• /
• pp.1-11
• /
• 2023

Large language models seem promising for handling reasoning problems, but their underlying solving mechanisms remain unclear. Large language models will establish a new paradigm in artificial intelligence and the society as a whole. However, a major challenge of large language models is the massive resources required for training and operation. To address this issue, researchers are actively exploring compact large language models that retain the capabilities of large language models while notably reducing the model size. These research efforts are mainly focused on improving pretraining, instruction tuning, and alignment. On the other hand, chain-of-thought prompting is a technique aimed at enhancing the reasoning ability of large language models. It provides an answer through a series of intermediate reasoning steps when given a problem. By guiding the model through a multistep problem-solving process, chain-of-thought prompting may improve the model reasoning skills. Mathematical reasoning, which is a fundamental aspect of human intelligence, has played a crucial role in advancing large language models toward human-level performance. As a result, mathematical reasoning is being widely explored in the context of large language models. This type of research extends to various domains such as geometry problem solving, tabular mathematical reasoning, visual question answering, and other areas.

• English Language & Literature Teaching
• /
• v.11 no.4
• /
• pp.121-137
• /
• 2005

The present study aims to examine how the roles of teacher and learners affect the repair patterns of both teacher's and learner's utterances in English as a second language (ESL) classroom discourse. The study analyzed beginning ESL classroom discourse and found that the structure of repair seems to be greatly influenced by the roles of participants in a second language classroom. The teacher's repair work was mainly characterized by self-repair. In contrast, learners' repair sequences were predominantly characterized by other-repair. More specifically, self-initiation by the learner of the trouble source was cooperatively completed by the teacher and the other learners. Other-initiated and other-completed repair was the most prevalent form in the current classroom data, which was carried out by the teacher in both modulated and unmodulated manners. When the trouble sources were mostly concerned with the learners' problems with linguistic competence and information presented in the textbook, other-repair took place in a modulated manner (i.e., recasting and prompting). On the other hand, when dealing with learners' errors with factual knowledge, other-repair was conducted in an unmodulated way (i.e., 'no' plus correction).

• Fashion & Textile Research Journal
• /
• v.18 no.4
• /
• pp.468-476
• /
• 2016

Recent advancements in optics technology enable us to realize fast scans of hands using two-dimensional (2D) image scanners. In this paper, we propose an automatic hand measurement system using 2D image scanners for customized glove production. To develop the automatic hand measurement system, firstly hand scanning devices has been constructed. The devices are designed to block external lights and have user interface to guide hand posture during scanning. After hands are scanned, hand contour is extracted using binary image processing, noise elimination and outline tracing. And then, 19 hand landmarks are automatically detected using an automatic hand landmark detection algorithm based on geometric feature analysis. Then, automatic hand measurement program is executed based on the automatically extracted landmarks and measurement algorithms. The automatic hand measurement algorithms have been developed for 18 hand measurements required for custom-made glove pattern making. The program has been coded using the C++ programming language. We have implemented experiments to demonstrate the validity of the system using 11 subjects (8 males, 3 females) by comparing automatic 2D scan measurements with manual measurements. The result shows that the automatic 2D scan measurements are acceptable in the customized glove making industry. Our evaluation results confirm its effectiveness and robustness.

• Journal of Korean language education
• /
• v.29 no.1
• /
• pp.85-108
• /
• 2018

This study pointed out the reality that many novice Korean language teachers who lack rater training are scoring the learners' writing skill. The study performed and analyzed a case where pre-service teachers were educated in order to explore the possibility of promoting rater training in a Korean language teacher training course. The pre-service teachers majoring in Korean language education at the graduate school scored TOPIK compositions and were provided feedback by the FACETS program, which were further discussed at the rater meeting. In three scoring processes, the raters scored with conscious of own rating patterns and showed positive change or over correction due to excessive consciousness. Consequentially, ongoing training can improve rating ability, and considering the fact that professional rater training is hard to progress, the method composed of FACETS analysis and rater training revealed positive effects. On the other hand, the rater training including native Korean and non-native(Chinese) speakers together showed no significant difference by mother tongue but by individual difference. This can be interpreted as a positive implication to the rating reliability of non-native speakers possessing advanced Korean language abilities. However, this must be supplemented through extended research.