• Journal of Advanced Marine Engineering and Technology
• /
• v.39 no.2
• /
• pp.172-178
• /
• 2015

Constructing a bilingual multi-word lexicon is confronted with many difficulties such as an absence of a commonly accepted gold-standard dataset. Besides, in fact, there is no everybody's definition of what a multi-word unit is. In considering these problems, this paper evaluates and analyzes the context vector approach which is one of a novel alignment method of constructing bilingual lexicons from parallel corpora, by comparing with one of general methods. The approach builds context vectors for both source and target single-word units from two parallel corpora. To adapt the approach to multi-word units, we identify all multi-word candidates (namely noun phrases in this work) first, and then concatenate them into single-word units. As a result, therefore, we can use the context vector approach to satisfy our need for multi-word units. In our experimental results, the context vector approach has shown stronger performance over the other approach. The contribution of the paper is analyzing the various types of errors for the experimental results. For the future works, we will study the similarity measure that not only covers a multi-word unit itself but also covers its constituents.

• KIPS Transactions on Software and Data Engineering
• /
• v.5 no.11
• /
• pp.563-568
• /
• 2016

The word sense disambiguation problem is to find the correct sense of an ambiguous word having multiple senses in a dictionary in a sentence. We regard this problem as a multi-class classification problem and classify the ambiguous word by using Support Vector Machines. Context words of the ambiguous word, which are extracted from Sejong sense tagged corpus, are represented to two kinds of vector space. One vector space is composed of context words vectors having binary weights. The other vector space has vectors where the context words are mapped by word embedding model. After experiments, we acquired accuracy of 87.0% with context word vectors and 86.0% with word embedding model.

• Journal of Korea Multimedia Society
• /
• v.24 no.10
• /
• pp.1391-1402
• /
• 2021

This paper focuses use context-sensitive spelling error correction using generative adversarial network. Generative adversarial network[1] are attracting attention as they solve data generation problems that have been a challenge in the field of deep learning. In this paper, sentences are generated using word embedding information and reflected in word distribution representation. We experiment with DCGAN[2] used for the stability of learning in the existing image processing and D2GAN[3] with double discriminator. In this paper, we experimented with how the composition of generative adversarial networks and the change of learning corpus influence the context-sensitive spelling error correction In the experiment, we correction the generated word embedding information and compare the performance with the actual word embedding information.

• Phonetics and Speech Sciences
• /
• v.7 no.3
• /
• pp.165-173
• /
• 2015

This study was aim to compare the phonological error patterns and PCC(Percentage of Correct Consonants) derived from the single word and spontaneous speech contexts of the speech sound disorders with unknown origin(SSD). The present study suggest that the development phonological error patterns and non-developmental error patterns of the target children, in according to speech context. The subjects were 15 children with SSD up to the age of 5 from 3 years of age. This research use 37 words of APAC(Assessment of Phonology & Articulation for Children) in the single word context and 100 eojeol in the spontaneous speech context. There was no difference of PCC between the single word and the spontaneous speech contexts. Significantly different developmental phonological error patterns between the single word and the spontaneous speech contexts were syllable deletion, word-medial onset deletion, liquid deletion, gliding, affrication, fricative other error, tensing, regressive assimilation. Significantly different non-developmental phonological error patterns were backing, addtion of phoneme, aspirating. The study showed that there was no difference of PCC between elicited single word and spontaneous conversational context. And there were some different phonological error patterns derived from the two contexts of the speech sound disorders. The more important interventions target is the error patterns of the spontaneous speech contexts for the immediate generalization and rising overall intelligibility.

• Education of Primary School Mathematics
• /
• v.25 no.4
• /
• pp.297-312
• /
• 2022

Word problems can lead learners to more meaningfully learn mathematics by providing learners with various problem-solving experiences and guiding them to apply mathematical knowledge to the context. This study attempted to provide implications for the textbook writing and teaching and learning process by examining the word problem of elementary mathematics textbooks from the perspective of practical context. The word problem of elementary mathematics textbooks was examined, and elementary mathematics textbooks in the United States and Finland were referenced to find specific alternatives. As a result, when setting an unnatural context or subject to the word problem in elementary mathematics textbooks, artificial numbers were inserted or verbal expressions and illustrations were presented unclearly. In this case, it may be difficult for learners to recognize the context of the word problem as separate from real life or to solve the problem by understanding the content required by the word problem. In the future, it is necessary to organize various types of word problems in practical contexts, such as setting up situations in consideration of learners in textbooks, actively using illustrations and diagrams, and organizing verbal expressions and illustrations more clearly.

• Journal of Korea Multimedia Society
• /
• v.25 no.3
• /
• pp.493-501
• /
• 2022

This paper is a study on context-sensitive spelling error correction and uses the Korean WordNet (KorLex)[1] that defines the relationship between words as a graph to improve the performance of the correction[2] based on the vector information of the word embedded in the correction technique. The Korean WordNet replaced WordNet[3] developed at Princeton University in the United States and was additionally constructed for Korean. In order to learn a semantic network in graph form or to use it for learned vector information, it is necessary to transform it into a vector form by embedding learning. For transformation, we list the nodes (limited number) in a line format like a sentence in a graph in the form of a network before the training input. One of the learning techniques that use this strategy is Deepwalk[4]. DeepWalk is used to learn graphs between words in the Korean WordNet. The graph embedding information is used in concatenation with the word vector information of the learned language model for correction, and the final correction word is determined by the cosine distance value between the vectors. In this paper, In order to test whether the information of graph embedding affects the improvement of the performance of context- sensitive spelling error correction, a confused word pair was constructed and tested from the perspective of Word Sense Disambiguation(WSD). In the experimental results, the average correction performance of all confused word pairs was improved by 2.24% compared to the baseline correction performance.

• Journal of Advanced Marine Engineering and Technology
• /
• v.38 no.4
• /
• pp.444-450
• /
• 2014

Most researches on word sense disambiguation have used static sized context regardless of sentence patterns. This paper proposes to use dynamic sized context considering sentence patterns and distance between words for word sense disambiguation. We evaluated our system 12 words in 32,735sentences with Sejong POS and sense tagged corpus, and dynamic sized context showed 92.2% average accuracy for predicates, which is better than accuracy of static sized context.

• Korean Journal of Cognitive Science
• /
• v.20 no.3
• /
• pp.243-274
• /
• 2009

The association, word frequency and imagery have been considered as the main factors that affect the word recognition. The present study aimed to examine the imagery effect and the interaction of the association effect while controlling the frequency effect. To explain the imagery effect, we compared the two theories (dual-coding theory, context availability model). The lexical decision task using priming paradigm was administered. The duration of prime words was manipulated as 20ms, 50ms, and 450ms in experiments 1, 2, and 3, respectively. The association and imagery of prime words were manipulated as the main factors in each of the three experiments. In experiment 1, the duration of prime words (20ms) which is expected to not activate the semantic context enough to affects the word recognition was used. As a result, only imagery effect was statically significant. In experiment 2, the duration of prime word was 50ms, which we expected to activate the semantic context without perceptual awareness. The result showed both the association and imagery effects. The interaction between the two effects was also significant. In experiment 3, to activate the semantic context with perceptual awareness, the prime words were presented for 450ms. Only association effect was statically significant in this experimental condition. The results of the three experiments suggest that the influence of the imagery was at the early stages of word recognition, while the association effect appeared rather later than the imagery. These results implied that the two theories are not contrary to each other. The dual-coding theory just concerned imagery effect which affects the early stage of word recognition, and context-availability model is more for the semantic context effect which affects rather later stage of word recognition. To explain the word recognition process more completely, some integrated model need to be developed considering not only the main 3 effects but also the stages which extends along the time course of the process.

• Phonetics and Speech Sciences
• /
• v.7 no.2
• /
• pp.3-8
• /
• 2015

Denasalization that nasals are replaced by stops is an unusual error pattern related to manner of articulation. The purpose of this study is to investigate the prevalence of denasalization and to scrutinize the nasal production according to phonological context for typically developing children and children with speech sound disorders(SSD). 220 typically developing children and 48 SSD children from 2~6 years of age were tested with a formal word test, and those who demonstrate denasalization were selected. In addition, the nasal production of SSD children with denasalization were analyzed for the correctness and the error types using the formal word test and spontaneous conversation. The results were as follows: (1) Denasalization was shown in below 10% of 2-3 years of age with typically developing children and in above 20% of 2-5 years of age with SSD. (2) The SSD children who demonstrate denasalization were categorized into 4 types according to the error context of nasals; nasal errors with all word positions, nasal errors with word-final and word-medial positions, nasal errors with word-medial position preceding vowels, and nasal errors with word-medial position preceding obstruents. These results indicate that denasalization is a clinically important error pattern, and word-medial position preceding obstruents is an essential context for denasalization in terms of Korean phonotactics.

• Journal of Information Management
• /
• v.42 no.2
• /
• pp.193-210
• /
• 2011

The study was applied to context window sizes and weighting method to obtain the best performance of word sense disambiguation using support vector machine. The context window sizes were used to a 3-word, sentence, 50-bytes, and document window around the targeted word. The weighting methods were used to Binary, Term Frequency(TF), TF ${\times}$ Inverse Document Frequency(IDF), and Log TF ${\times}$ IDF. As a result, the performance of 50-bytes in the context window size was best. The Binary weighting method showed the best performance.