• MALSORI
• /
• no.59
• /
• pp.53-68
• /
• 2006

We report the evaluation results of the Korean speech recognition platform called ECHOS. The platform has an object-oriented and reusable architecture so that researchers can easily evaluate their own algorithms. The platform has all intrinsic modules to build a large vocabulary speech recognizer: Noise reduction, end-point detection, feature extraction, hidden Markov model (HMM)-based acoustic modeling, cross-word modeling, n-gram language modeling, n-best search, word graph generation, and Korean-specific language processing. The platform supports both lexical search trees and finite-state networks. It performs word-dependent n-best search with bigram in the forward search stage, and rescores the lattice with trigram in the backward stage. In an 8000-word continuous speech recognition task, the platform with a lexical tree increases 40% of word errors but decreases 50% of recognition time compared to the HTK platform with flat lexicon. ECHOS reduces 40% of recognition errors through incorporation of cross-word modeling. With the number of Gaussian mixtures increasing to 16, it yields word accuracy comparable to the previous lexical tree-based platform, Julius.

• Journal of Korea Multimedia Society
• /
• v.9 no.12
• /
• pp.1607-1616
• /
• 2006

The growing market of multimedia and digital signal processing requires significant data-path portions of SoCs. However, the common models for verification are not suitable for SoCs. A novel model--WGL (Weighted Generalized List) is proposed, which is based on the general-list decomposition of polynomials, with three different weights and manipulation rules introduced to effect node sharing and the canonicity. Timing parameters and operations on them are also considered. Examples show the word-level WGL is the only model to linearly represent the common word-level functions and the bit-level WGL is especially suitable for arithmetic intensive circuits. The model is proved to be a uniform and efficient model for both bit-level and word-level functions. Then Based on the WGL model, a backward-construction logic-verification approach is presented, which reduces time and space complexity for multipliers to polynomial complexity(time complexity is less than $O(n^{3.6})$ and space complexity is less than $O(n^{1.5})$) without hierarchical partitioning. Finally, a construction methodology of word-level polynomials is also presented in order to implement complex high-level verification, which combines order computation and coefficient solving, and adopts an efficient backward approach. The construction complexity is much less than the existing ones, e.g. the construction time for multipliers grows at the power of less than 1.6 in the size of the input word without increasing the maximal space required. The WGL model and the verification methods based on WGL show their theoretical and applicable significance in SoC design.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.2C
• /
• pp.348-353
• /
• 2004

Development of an efficient and secure payment system is prerequisite for the construction of electronic payment mechanism in mobile environment. Since current PayWord protocol system generates vendor's certificate for each transaction, it requires lot of operation for transaction. In this paper, we use a session key generated by ID-based tripartite Key agreement protocol which use an Elliptic Curve Cryptosystem over finite field $F_{q}$ for transactions. Therefore, our protocol reduces algorithm operations. In particular, proposed protocol using ID-based public key cryptosystem has the advantages over the existing systems in speed and it is more secure in Man-in-the-middle attacks and Forward secrecy.

• The Journal of Information Systems
• /
• v.30 no.2
• /
• pp.1-27
• /
• 2021

Purpose Even if many startups firms have developed innovative items and a potential for success, they often have a limited financial resources, which makes them difficult to do business. To overcome this financial difficulty, startups have used one of fintech services, called crowdfunding that can be a good alternative to solving the difficulty of financing. The purpose of this study is to empirically validate the proposed research model that investigates the reasons of trusting crowdfunding platform, which positively leads to two outcomes - intention to participate and word-of-mouth for reward-based crowdfunding project. Design/methodology/approach We proposed several factors categorized as trust, information quality, and platform traits that have a positive impact on trust of crowdfunding platform, which positively leads to intention to participate and word-of-mouth of crowdfunding. The collected(n=285) from individuals who have participated in crowdfunding project was analyzed with SmartPLS 3.0 to test proposed hypotheses. Findings The results showed that all proposed variables (website reputation, crowdfunding familiarity, digital storytelling, information quality, and interaction) had a significant impact on crowfunding platform trust with exception of product differentiation. In addition, crowfunding platform trust was positively associated with participating intention and word-of-mouth. Based on findings, we discussed the research results and implication alone with a direction for future studies.

• School Mathematics
• /
• v.11 no.3
• /
• pp.497-511
• /
• 2009

This study compared two problem solving instructional approaches, schema based sequence instruction and schema based parallel instruction on word problem solving performance of elementary school students who were in general students group. The subjects totaled 48 third grade students who were exposed to a test that consisted of 9 word problem items of three types for 4 sessions. First of all, the baseline of word problem performance level was measured without any training. During session 1, 2 and 3 participants were put into strategic training groups. The experiment was designed by two between factor(two intervention group and two within factors(two problem types, three sessions). The results of experiment were as follows. Schema based sequence instruction group performed significantly better than students in another group on word problem solving performance. The effect of strategic schema based Instruction revealed that solving word problems relied upon problem types, sessions and input orders which were of great value.

• Proceedings of the Acoustical Society of Korea Conference
• /
• 1998.08a
• /
• pp.293-297
• /
• 1998

전화망에서의 연결 숫자 인식 시스템의 개발에 대한 내용을 다루며, 이 시스템에서 다양한 숫자 모델링 방법들을 구현하고 비겨하였다. Word 모델의 경우 문맥독립 whole-word 모델을 구현하였으며, sub-word 모델로는 triphone 모델과 불파음화 자음을 모음에 포함시킨 modified triphone 모델을 구현하였다. 그리고 tree-based clustering 방법을 sub-word 모델과 문맥종속 whole-word 모델에 적용하였다. 이와 같은 숫자모델들에 대해 연속 HMM을 이용하여 화자독립 연결숫자 인식 실험을 수행한 결과, 문맥종속 단어 모델이 문맥독립 단어 모델보다 우수한 성능을 나타냈으며, triphone 모델과 modified triphone 모델은 유사한 성능을 나타냈다. 특히 tree-based clustering 방법을 적용한 문맥종속 단어 모델이 4연 숫자열에 대해 99.8%의 단어 dsltlr률 및 99.1%의 숫자열 인식률로서 가장 우수한 성능을 나타내었다.

• Asia Pacific Journal of Corpus Research
• /
• v.1 no.2
• /
• pp.41-56
• /
• 2020

This paper aims to investigate how word order interacts with cliticization in Sakizaya, a Formosan language. This paper looks into nominative and genitive case markers from a corpus-based approach. The data are collected from an online dictionary of Sakizaya, and they are classified into two word orders: nominative case marker preceding genitive case marker and vice versa. The data are also divided into three categories, according to the demarcation of the case markers, which include right, left, or no demarcation. The corpus includes 700 sentences in the construction of predicate + noun phrase + noun phrase. The results suggest that the two case markers tend to be parsed into the preceding word and show right demarcation. The results also reveal that there are type difference and distance effect of the case markers on the cliticization. Nominative case markers show more right demarcation than genitive case markers do in the corpus. Also, the closer the case markers are to the predicate, the more possible the case markers undergo cliticization.

• Asia Pacific Journal of Corpus Research
• /
• v.4 no.2
• /
• pp.57-74
• /
• 2023

Having a firm grasp of technical terms is essential for learners of Japanese for Specific Purposes (JSP). This research aims to analyze Japanese nursing care vocabulary based on objective corpus-based frequency and subjectively rated word familiarity. For this purpose, we constructed a text corpus centered on the National Examination for Certified Care Workers to extract nursing care keywords. The Log-Likelihood Ratio (LLR) was used as the statistical criterion for keyword identification, giving a list of 300 keywords as target words for a further word recognition survey. The survey involved 115 participants of whom 51 were certified care workers (CW group) and 64 were individuals from the general public (GP group). These participants rated the familiarity of the target keywords through crowdsourcing. Given the limited sample size, Bayesian linear mixed models were utilized to determine word familiarity rates. Our study conducted a comparative analysis of word familiarity between the CW group and the GP group, revealing key terms that are crucial for professionals but potentially unfamiliar to the general public. By focusing on these terms, instructors can bridge the knowledge gap more efficiently.

• Journal of Korean Institute of Industrial Engineers
• /
• v.40 no.1
• /
• pp.18-33
• /
• 2014

A Word is the smallest unit for text analysis, and the premise behind most text-mining algorithms is that the words in given documents can be perfectly recognized. However, the newly coined words, spelling and spacing errors, and domain adaptation problems make it difficult to recognize words correctly. To make matters worse, obtaining a sufficient amount of training data that can be used in any situation is not only unrealistic but also inefficient. Therefore, an automatical word extraction method which does not require a training process is desperately needed. WordRank, the most widely used unsupervised word extraction algorithm for Chinese and Japanese, shows a poor word extraction performance in Korean due to different language structures. In this paper, we first discuss why WordRank has a poor performance in Korean, and propose a customized WordRank algorithm for Korean, named KR-WordRank, by considering its linguistic characteristics and by improving the robustness to noise in text documents. Experiment results show that the performance of KR-WordRank is significantly better than that of the original WordRank in Korean. In addition, it is found that not only can our proposed algorithm extract proper words but also identify candidate keywords for an effective document summarization.

• Journal of the Korean Society for Library and Information Science
• /
• v.55 no.4
• /
• pp.115-140
• /
• 2021

This study divided the keyword sets searched from LISTA database focusing on the overseas open access fields into two types (controlled keywords and uncontrolled keywords), and examined the results of performing an intellectual structure analysis based on profiling for the each keyword type. In addition, these results were compared with those of an intellectual structural analysis based on co-word analysis. Through this, I tried to investigate whether similar results were derived from profiling, another method of intellectual structure analysis, and to examine the differences between co-word analysis and profiling results. As a result, there was a similar difference to the co-word analysis in the results of intellectual structure analysis based on profiling for each of the two keyword types. Also, there were also noticeable differences between the results of intellectual structural analysis based on profiling and co-word analysis. Therefore, intellectual structure analysis using keywords should consider the characteristics of each keyword type according to the research purpose, and better results can be expected to be used based on profiling than co-word analysis to more clearly understand research trends in a specific field.