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Journal articles on the topic 'Chinese characters'
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1
ZANG, Kehe. "Chinese Characters, the Science of Chinese Characters, Subject of Chinese Characters." International Journal of Chinese Character Studies 1, no. 2 (December 30, 2015): 55–74. http://dx.doi.org/10.18369/waccs.2015.1.55.
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Niu, Yunbo. "A Review and Prospects of Chinese Character Research in the Last Thirty Years." SHS Web of Conferences 167 (2023): 02019. http://dx.doi.org/10.1051/shsconf/202316702019.
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At this stage, the study of Chinese characters is undergoing a transformation of modern applications and technology, and research in this field is both deeply rooted in the traditional Chinese study of script and flourishing with new vitality. This paper analyses the five major components of Chinese character research, namely, the study of archaic characters, the study of the phonology, morphology and meaning of Chinese characters, the study of the application of Chinese characters in the computer field, the study of the cognitive processing of Chinese characters, and the study of Chinese character teaching, and the three methods of Chinese character research, namely, exegetical examination, corpus database and empirical research methods. This paper summarizes the literature on Chinese character research, analyses the trends in Chinese character research, and summarizes the review and outlook of Chinese character research in the past thirty years.
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KWAK, HYUN SUK. "A Study on the Moral Characteristics of Chinese Characters Marked as “華[Hua]” in 漢鮮文新玉篇(HànXiānWénXīnYùPiān)." Society for Chinese Humanities in Korea 86 (April 30, 2024): 37–57. http://dx.doi.org/10.35955/jch.2024.04.86.37.
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The Han 漢鮮文新玉篇(HànXiānWénXīnYùPiān) was an attempt to compile an autobiography suitable for the times by examining newly created new Chinese characters, Japanese characters, and Chinese characters among the autobiographies compiled in the modern period, you can see Chinese characters with the notation of “華[Hua]” in the Chinese commentary of 漢鮮文新玉篇(HànXiānWénXīnYùPiān). The Chinese characters with this sign are said to be 'Chinese characters (language)' used in China, it is necessary to examine whether this is really a Chinese character used in China, and if so, what its properties are. herefore, as part of a study to identify the properties of Chinese characters marked as “華[Hua]”, this paper intends to extract data from Chinese characters marked as “華[Hua]” in 漢鮮文新玉篇(HànXiānWénXīnYùPiān), in addition, the morphological characteristics of the Chinese characters marked “華[Hua]” were considered. The results are as follows. First, there are a total of 90 Chinese characters written as “華[Hua]” in 漢鮮文新玉篇(HànXiānWénXīnYùPiān). Among them, there are a total of 35 Chinese characters that can be found in old records but are explained by replacing them with other letters. These Chinese characters showed structural differences such as differences in strokes, differences in one-sidedness, and use of other letters. All of these were divided into cases where the subject was a 俗字 and the case where the subject was a 俗字 character because of the transfer between letters, and the subject was taken with the representativeness of the time centered on the 俗字 character. Second, in the Chinese annotation of Chinese characters with the notation of “華[Hua]” in 漢鮮文新玉篇(HànXiānWénXīnYùPiān), the form and word order of Chinese characters in which Chinese characters exist could be divided into five categories: (1) simple row type/order relationship type/parallel relationship type, (2) predicate-object structure/subject-order structure type, (3) predicate-bore structure type, (4) formal relationship type, and (5) other types. Third, it is a Chinese character that does not exist in the Chinese annotation of Chinese characters with the notation of “華[Hua]” in 漢鮮文新玉篇(HànXiānWénXīnYùPiān). At that time, the font and meaning exist in Korea, but the meaning of the Chinese character marked “華[Hua]” is mainly used in China.
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Chua, Hui Wen, Hui Ling Lee, Suhaida Omar, Mahama Tohleheng, and Siao Mei Chin. "Malaysian Non-native Chinese Students' Challenges and Learning Strategies in Chinese Characters Learning." EDUCATUM Journal of Social Sciences 8, no. 1 (June 29, 2022): 67–82. http://dx.doi.org/10.37134/ejoss.vol8.1.7.2022.
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This study investigates the challenges faced by non-native Chinese learners in learning Chinese characters and their learning strategies. This research applied quantitative research, where the questionnaire was delivered at the end of the semester to 370 students of Mandarin level two, selected through convenience sampling. The descriptive analysis showed that most of the students stated that being literate in Chinese characters and learning many Chinese characters was the most challenging act while corresponding between characters and their pronunciations was the least challenging. Next, the students listed repetitively memorising Chinese characters as the preferred learning strategy, followed by imitating each stroke of a Chinese character and picturing what Chinese characters look like in their minds. The finding of this study contradicts other research studies since the students in this study did not perceive the "lack of correspondence between characters and their pronunciation in Chinese character learning" as the main challenge since they only learned 105 Chinese characters for two semesters. Nonetheless, this study also supports similar research on learning strategies in that students have difficulty learning Chinese characters as there are too many characters, too many pronunciations, and too many strokes. Hence, they repeatedly imitate and memorise the characters as learning strategies. Thus, memory strategies and graphic strategies are the main learning strategies to help learners cope with learning Chinese characters. For future study, it is recommended to find out whether there is any correlation between the challenges for non-native Chinese learners and the learning strategies they apply, which will give teachers an idea of how to improve their teaching to support learners’ learning strategies to boost their Chinese character learning.
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Kim, Byoung-ju. "A Study on the Chinese Character Education Method for Beginners in Chinese Character: Focused on the Strokes of Chinese characters." Korean Society of Calligraphy 44 (March 30, 2024): 193–216. http://dx.doi.org/10.19077/tsoc.2023.44.7.
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The purpose of this article was to explore new ways of teaching Chinese characters based on the cognitive patterns that learners have in advance. To this end, we identified the cognitive patterns of beginners who first encountered Chinese characters and presented teaching Chinese character and contents to suit their cognitive styles.
The learning habits of most beginners who first encountered Chinese characters is familiar with the learning habits of acquiring Hangeul and English. It is very difficult to expand the learning habits by adjusting the existing learning habits. Based on these points, the school devised a way to start Chinese character education in the existing learning habits framework. The method is to start Chinese character education by using strokes. The stroke can serve as the alphabet of Hangeul and the alphabet of English, making it a material for learners to easily access Chinese characters with a priori learning habits. In this article, the author suggested that strokes be classified into 20 categories and each stroke should be named and used for teaching Chinese character.
It is important to determine the learner's step-by-step learning according to the curriculum of education. It could be a way of teaching Chinese characters to teach them first when they first start Chinese characters. Still, strokes education is still unfamiliar as an educational method for Chinese characters. However, we hope that it will be a way for beginners who are new to Chinese characters to gain easier access to learning them.
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Kim, Byoung-ju. "A Study on the Chinese Character Education Method for Beginners in Chinese Character: Focused on the Strokes of Chinese characters." Korean Society of Calligraphy 44 (March 30, 2024): 193–216. http://dx.doi.org/10.19077/tsoc.2024.44.7.
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The purpose of this article was to explore new ways of teaching Chinese characters based on the cognitive patterns that learners have in advance. To this end, we identified the cognitive patterns of beginners who first encountered Chinese characters and presented teaching Chinese character and contents to suit their cognitive styles.
The learning habits of most beginners who first encountered Chinese characters is familiar with the learning habits of acquiring Hangeul and English. It is very difficult to expand the learning habits by adjusting the existing learning habits. Based on these points, the school devised a way to start Chinese character education in the existing learning habits framework. The method is to start Chinese character education by using strokes. The stroke can serve as the alphabet of Hangeul and the alphabet of English, making it a material for learners to easily access Chinese characters with a priori learning habits. In this article, the author suggested that strokes be classified into 20 categories and each stroke should be named and used for teaching Chinese character.
It is important to determine the learner's step-by-step learning according to the curriculum of education. It could be a way of teaching Chinese characters to teach them first when they first start Chinese characters. Still, strokes education is still unfamiliar as an educational method for Chinese characters. However, we hope that it will be a way for beginners who are new to Chinese characters to gain easier access to learning them.
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Huynh, Duc Du. "Ancient Vietnamese scholars’ views on Chinese characters." Journal of Chinese Writing Systems 7, no. 1 (March 2023): 22–34. http://dx.doi.org/10.1177/25138502221147951.
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Based on the preface and postscript in Vietnamese Chinese dictionaries and related documents, this article comprehensively compares the similarities and differences between the ancient Chinese and Vietnamese views of Chinese characters from the perspectives of the origin of Chinese characters, the introduction of Chinese characters, the relationship between Chinese characters and Nom characters, the survival and development of Chinese characters, the variation of Chinese character forms, and the morphological and phonological values of Chinese characters. It summarizes the inheritance and variation of Chinese characters in Vietnam, and attempts to provide a new perspective for studies related to the history of the development of Vietnamese Chinese characters and the history of the spread of Chinese characters.
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Rai, Laxmisha, and Hong Li. "MyOcrTool: Visualization System for Generating Associative Images of Chinese Characters in Smart Devices." Complexity 2021 (May 7, 2021): 1–14. http://dx.doi.org/10.1155/2021/5583287.
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Majority of Chinese characters are pictographic characters with strong associative ability and when a character appears for Chinese readers, they usually associate with the objects, or actions related to the character immediately. Having this background, we propose a system to visualize the simplified Chinese characters, so that developing any skills of either reading or writing Chinese characters is not necessary. Considering the extensive use and application of mobile devices, automatic identification of Chinese characters and display of associative images are made possible in smart devices to facilitate quick overview of a Chinese text. This work is of practical significance considering the research and development of real-time Chinese text recognition, display of associative images and for such users who would like to visualize the text with only images. The proposed Chinese character recognition system and visualization tool is named as MyOcrTool and developed for Android platform. The application recognizes the Chinese characters through OCR engine, and uses the internal voice playback interface to realize the audio functions and display the visual images of Chinese characters in real-time.
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CHENG, FANG-HSUAN, and WEN-HSING HSU. "RESEARCH ON CHINESE OCR IN TAIWAN." International Journal of Pattern Recognition and Artificial Intelligence 05, no. 01n02 (June 1991): 139–64. http://dx.doi.org/10.1142/s0218001491000107.
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This paper describes typical research on Chinese optical character recognition in Taiwan. Chinese characters can be represented by a set of basic line segments called strokes. Several approaches to the recognition of handwritten Chinese characters by stroke analysis are described here. A typical optical character recognition (OCR) system consists of four main parts: image preprocessing, feature extraction, radical extraction and matching. Image preprocessing is used to provide the suitable format for data processing. Feature extraction is used to extract stable features from the Chinese character. Radical extraction is used to decompose the Chinese character into radicals. Finally, matching is used to recognize the Chinese character. The reasons for using strokes as the features for Chinese character recognition are the following. First, all Chinese characters can be represented by a combination of strokes. Second, the algorithms developed under the concept of strokes do not have to be modified when the number of characters increases. Therefore, the algorithms described in this paper are suitable for recognizing large sets of Chinese characters.
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WANG, YING, and CATHERINE MCBRIDE. "Character reading and word reading in Chinese: Unique correlates for Chinese kindergarteners." Applied Psycholinguistics 37, no. 2 (April 8, 2015): 371–86. http://dx.doi.org/10.1017/s014271641500003x.
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ABSTRACTWe considered the extent to which learning to read Chinese characters and Chinese words (operationally defined as composed of two or more characters) are different in the present study. Study 1 compared reading of the same characters in isolation and those in the context of known words for 63 Chinese third-year kindergarteners. Results showed that children performed significantly better on reading the same characters when embedded within words than when alone. Study 2 further examined the correlates of single-character reading and two-character word reading for 142 Chinese third-year kindergarteners. Despite a high correlation between character reading and word reading, unique correlates emerged. Orthographic awareness, rapid automatized naming, and Pinyin letter-name knowledge independently explained variance in both character and word reading; however, orthographic awareness explained unique variance in character reading even after statistically controlling for word reading. Whereas orthographic and Pinyin knowledge may be more strongly associated with character recognition, other skills may be more important for learning to read words. Character and word reading may constitute slightly different processes, with somewhat different educational implications for each.
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Park, Jangkyoung, Ammar Ul Hassan, and Jaeyoung Choi. "CCFont: Component-Based Chinese Font Generation Model Using Generative Adversarial Networks (GANs)." Applied Sciences 12, no. 16 (August 10, 2022): 8005. http://dx.doi.org/10.3390/app12168005.
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Font generation using deep learning has made considerable progress using image style transfer, but the automatic conversion/generation of Chinese characters still remains a difficult task owing to the complex character shape and large number of Chinese characters. Most known Chinese character generation models use the image conversion method of the Chinese character shape itself; however, it is difficult to reproduce complex Chinese characters. Recent methods have utilized character compositionality by separating up to three or four components to improve the quality of generated characters, but it is still difficult to generate high-quality results for complex Chinese characters with many components. In this study, we proposed the CCFont model (component-based Chinese font generation model using generative adversarial networks (GANs)) that automatically generates all Chinese characters using Chinese character components (up to 17 components). The CCFont model generates all Chinese characters in various styles using the components of Chinese characters based on conditional GAN. By acquiring local style information from the components, the information is more accurate and there is less information loss than when global information is obtained from the image of the entire character, reducing the failure of style conversion and improving quality to produce high-quality results. Additionally, the CCFont model generates high-quality results without any additional training (zero-shot font generation without any additional training) for the first-seen characters and styles. For example, the CCFont model, which was trained with only traditional Chinese (TC) characters, generates high-quality results for languages that can be divided into components, such as Korean and Thai, as well as simplified Chinese (SC) characters that are only seen during inference. CCFont can be adopted as a multi-lingual font-generation model that can be applied to all languages, which can be divided into components. To the best of our knowledge, the proposed method is the first to generate a zero-shot multilingual generation model using components. Qualitative and quantitative experiments were conducted to demonstrate the effectiveness of the proposed method.
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f, f. "Study of the Construction of Meaning for the Component '目' in 'Shuowen Jiezi'." Society for Chinese Humanities in Korea 85 (December 31, 2023): 169–91. http://dx.doi.org/10.35955/jch.2023.12.85.169.
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Chinese characters are ideograms, formed based on their meanings. The concept of 'construction of meaning' (構意) in Chinese characters refers to the semantic information encapsulated in their forms, representing the subjective intent of the character's creator. In other words, the 'construction of meaning' is the semantic information that undergoes cognitive processing to be encapsulated in a visual form. Therefore, by studying the 'construction of meaning' of the components (構件) in Chinese characters, we can examine the process through which Chinese characters develop their unique semantic systems. This paper selects the 'Shuowen Jiezi', which interprets the 'construction of meaning' of the character forms in Shuowen based on the principle of 'unity of form and meaning', as its research material. To analyze the 'construction of meaning' of the component '目', this study categorized the character forms that include '目' into six types based on their semantic categories of actual meaning. As a result, it was found that the fundamental 'construction of meaning' of the component '目' is 'human eye', and the derived meaning, influenced by this fundamental concept, is 'window of the mind.
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Guruleva, Tatiana Leonidovna, and Alina Railevna Abdrakhmanova. "Decomposition structure of Chinese characters." Philology. Issues of Theory and Practice 17, no. 1 (January 11, 2024): 31–39. http://dx.doi.org/10.30853/phil20240005.
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The aim of the study is to systematically describe the decomposition structure of Chinese characters. The article contains a structural and categorical analysis of Chinese writing units. The scientific novelty of the research consists in the formulation of such a typological characteristic of Chinese character writing as lists, i.e., the constant need to compile various lists of characters and their components. These are lists of strokes; lists of characters; lists of indexing components; lists of indexing components series including lists of characters they form; lists of commonly used characters; lists of characters for learning Chinese as a foreign language, etc. As a result of analysing Russian and foreign scientific works on the research topic and the current language standards developed by the State Language and Writing Work Committee of the PRC (国家语言文字工作委员会), concepts and terms on the research topic (“stroke”, “character component”, “radical”, “indexing component”, “determinative”, “phonetic”) were clarified and systematised; the classification of character components depending on their location, the correlation between the concepts of the indexing component and the character component in diachrony and the structure of a hieroglyph in the process of its decomposition, i.e., in the process of breaking a hieroglyph into its constituent elements, were clarified.
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CHEN, LIN, CHARLES PERFETTI, YING LENG, and YOU LI. "Word superiority effect for native Chinese readers and low-proficiency Chinese learners." Applied Psycholinguistics 39, no. 6 (October 9, 2018): 1097–115. http://dx.doi.org/10.1017/s0142716418000255.
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ABSTRACTWritten word recognition in Chinese links the perception of individual characters with whole words. With experience in reading, a high-quality word representation can provide top-down influence on the perception of its constituent characters, thus producing a word superiority effect (WSE). In experiments using the Reicher–Wheeler paradigm, we examined the WSE in two-character words for native Chinese readers (Experiment 1) and low-proficiency adult Chinese learners with Thai (Experiment 2a) and Indonesian (Experiment 2b) as native language backgrounds. For native Chinese readers, the WSE was smaller for high-frequency than low-frequency characters, reflecting rapid access to more frequently experienced characters and a consequent reduction of top-down word-level effects. Learners of Chinese, however, showed a strong WSE for both low-frequency and high-frequency characters, reflecting less well-established character representations combined with word-level knowledge sufficient to support character recognition. The results suggest that native Chinese readers develop strong representations at both the character and the word level, while low-proficiency Chinese learners are more dependent on the word level. We discuss the possibility that a word-level emphasis Chinese foreign language instruction is one reason for this pattern.
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SUN, XINGMING, LIHUA YANG, Y. Y. TANG, and YUNFA HU. "A NEW STROKE EXTRACTION METHOD OF CHINESE CHARACTERS." International Journal of Pattern Recognition and Artificial Intelligence 15, no. 04 (June 2001): 707–21. http://dx.doi.org/10.1142/s0218001401001064.
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Stroke extraction of Chinese characters plays an important role in Chinese character information processing such as character recognition, document analysis, document compression and storage, font automation and so on. By analyzing the structure of Chinese characters deeply, this paper developed a novel method to extract strokes of Chinese characters directly from the original character pattern image. Two theorems, eight rules and an algorithm for stroke extraction of Chinese characters are presented. This method can overcome the difficulties encountered in disposing the intersection or connection of different strokes, and can eliminate noises successfully. Our experiments have shown that this method can extract strokes both accurately and efficiently.
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Nkrumah, Bright, and Raymond Asamoah. "Ghanaian Chinese Language Learners’ Perception of Chinese Characters." Journal of Foreign Language Teaching and Learning 7, no. 2 (October 12, 2022): 329–52. http://dx.doi.org/10.18196/ftl.v7i2.14077.
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This paper investigated students’ perception of learning Chinese characters at the University of Ghana. The Chinese writing system is an exclusive indispensable script that forms part of the Chinese culture. However, the complexity, forms, strokes, pronunciation, radicals, and orthography structure of the characters makes it difficult for Ghanaian students to learn the Chinese language. A qualitative and quantitative design was used for the study. Of 338 students, 183 participated in the study from the first to the fourth year. Purposive sampling was used to select the students to respond to the questionnaire and share their opinions about the Chinese characters in interviews. The findings showed that (a) reading and writing of the Chinese characters were perceived to be more difficult than speaking. (b) the Chinese character radicals, forms, remembering of strokes, orders, numbers, and the orthography structure of the Chinese characters were a hurdle for Chinese language learners. Suggestions were made to urge students to cultivate the habit of consistently practicing the characters through collective participation and learning. The language learners need to do away with excuses, fear, and make-believe obstructions and spend more time in the learning process to enhance their skills in the Chinese writing system.
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CUI, Peiling. "Chinese Characters and Chinese Humour." Journal of Chinese Characters 18 (August 31, 2017): 205–21. http://dx.doi.org/10.14772/cscck.2017.18.205.
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Simin, Huang. "PROBLEMS AND COUNTERMEASURES FOR ONLINE CHINESE CHARACTER TEACHING AT THE NATIONAL UNIVERSITY OF HUMANITIES IN UKRAINE." MODERN VECTORS OF SCIENCE AND EDUCATION DEVELOPMENT IN CHINA AND UKRAINE 2023, no. 9 (May 2023): 86–97. http://dx.doi.org/10.24195/2414-4746-2023-9-9.
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This paper analyses the teaching of Online Chinese characters to Ukrainian students. The author singles out two problems of Online Chinese characters teaching/learning at the National University of Humanities. According to the problems, four countermeasures of online Chinese characters teaching have been put forward: to strengthen the analysis of homophones and shapes, to improve the sound-speaking use, to maintain a tolerance to the Chinese characters, to strengthen the Chinese character consciousness, to attach importance to Pinyin teaching, and to use the real teaching corpus to improve online Chinese characters writing.
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Lim, Sugiato. "Impact of Mastering Traditional Characters to Learn Simplified Characters – In Analogy Simplified Picto-Phonogram Characters As Reference." Humaniora 5, no. 2 (October 30, 2014): 857. http://dx.doi.org/10.21512/humaniora.v5i2.3163.
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There are a number of Southeast Asian students begin to learn Chinese in their own country based on traditional Chinese characters. Therefore, author based on own learning experience talked about the influence of mastering traditional characters to learn simplified Chinese characters. By collecting the traditionalcharacter texts, summarizing the occurrence of error categories of simplified Chinese characters, and based on the Chinese character simplification methods in “Fan Jian Zi Duizhao Zidian”, research summed up the difficulties in learning Chinese simplified characters. This study was mainly based on the analogy simplified characters as the breakthrough point. The first part of this article introduces the classification of pictophonogram characters in simplified. The second part of the article introduces the impact of learning simplifiedChinese characters while learners get traditional characters background. The last part, article draws the conclusion that the impact of mastering traditional characters to learn simplified Chinese characters might be a double-edged sword. The proper understanding is helpful to the study of simplified characters, grasp the inappropriate is likely to mislead the learner.
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Zhang, Lingyi. "Yi Sheng Character Used in New Practical Chinese Reader Textbook (Volume 1-4)." Communications in Humanities Research 5, no. 1 (September 14, 2023): 110–16. http://dx.doi.org/10.54254/2753-7064/5/20230110.
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In view of the current situation that the teaching of Chinese characters' pronunciation is relatively separated from the font and meaning in Teaching Chinese as a Foreign Language (TCFL), this thesis puts forward a plan to introduce the concept of "Yi Sheng character" in Shuowen Jiezi based on the fundamental, practicability and innovative of the New Practical Chinese Reader Textbook (Volume 1-4). This thesis analyses all the Yi Sheng characters and Yi Sheng components mentioned in the "Basic Chinese Characters" section of the New Practical Chinese Reader Textbooks (Volumes 1-4), discusses their associations with modern pronunciation by ancient or modern pronunciation, traditional or simplified Chinese character and phonemic component, in a bid to summarise the associations in meanings between the Yi Sheng components and the Yi Sheng characters. In this way, foreign Chinese learners can gain a holistic understanding of the pronunciation-font-meaning combination of basic Chinese characters.
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Gao, Feng, Jingping Zhang, Yongge Liu, and Yahong Han. "Image Translation for Oracle Bone Character Interpretation." Symmetry 14, no. 4 (April 4, 2022): 743. http://dx.doi.org/10.3390/sym14040743.
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The Oracle Bone Characters are the earliest known ancient Chinese characters and are an important record of the civilization of ancient China.The interpretation of the Oracle Bone Characters is challenging and requires professional knowledge from ancient Chinese language experts. Although some works have utilized deep learning to perform image detection and recognition using the Oracle Bone Characters, these methods have proven difficult to use for the interpretation of uninterpreted Oracle Bone Character images. Inspired by the prior knowledge that there exists a relation between glyphs from Oracle Bone Character images and images of modern Chinese characters, we proposed a method of image translation from Oracle Bone Characters to modern Chinese characters based on the use of a generative adversarial network to capture the implicit relationship between glyphs from Oracle Bone Characters and modern Chinese characters. The image translation process between Oracle Bone Characters and the modern Chinese characters forms a symmetrical structure, comprising an encoder and decoder. To our knowledge, our symmetrical image translation method is the first of its kind used for the task of interpreting Oracle Bone Characters. Our experiments indicated that our image translation method can provide glyph information to aid in the interpretation of Oracle Bone Characters.
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Park, sejin. "Korean vocabulary education using Chinese characters adjacently in reading text." Barun Academy of History 11 (June 30, 2022): 257–79. http://dx.doi.org/10.55793/jkhc.2022.11.257.
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In this study, Chinese learners proposed Writing with Chinese characters adjacently as a way to increase the efficiency of learning Korean vocabulary and reading comprehension. To prove this justification, 30 Chinese international students currently studying at Korean universities were randomly selected and surveyed. In addition, the effectiveness of Writing with Chinese characters adjacently on reading education and vocabulary acquisition was examined by writing Chinese characters together in the "Chinese character vocabulary" melted in the learning textbook.
Accordingly, based on their background knowledge of Chinese characters, Chinese learners concluded that they not only easily understand the meaning of the text but also are effective in acquiring vocabulary. It should also not be overlooked that this can be an important motivation for learners in Chinese character cultures to learn Korean rather than learners in other cultures.
Based on the conclusions drawn here, it is possible to find new teachinglearning methods that can efficiently acquire Korean vocabulary and improve reading skills. In order for this Chinese character method to establish itself as a Korean language teaching method for Korean learners in the Chinese character culture, it must be actively applied to various textbooks such as Korean reading textbooks, Korean vocabulary learning textbooks, and major textbooks. And it is necessary to be sure that Writing with Chinese characters adjacently can be the best means of helping understand Korean language.
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Liu, Li Qun. "Cognate Characters and Chinese Characters Teaching." Han-Character and Classical written language Education 28 (May 30, 2012): 153–70. http://dx.doi.org/10.15670/hace.2012.28.1.153.
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Yang, won-seok. "Study Methodology of Chinese Characters Culturology and Chinese Characters Education." Han-Character and Classical written language Education 35 (September 30, 2014): 79–109. http://dx.doi.org/10.15670/hace.2014.35.1.79.
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Voon, Chen Huey, Tang Ker Shin, and Ng Wei Shean. "Chinese Character Recognition Using Non-negative Matrix Factorization." Jurnal Kejuruteraan 36, no. 2 (March 30, 2024): 653–60. http://dx.doi.org/10.17576/jkukm-2024-36(2)-24.
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Non-negative matrix factorization (NMF) was introduced by Paatero and Tapper in 1994 and it was a general way of reducing the dimension of the matrix with non-negative entries. Non-negative matrix factorization is very useful in many data analysis applications such as character recognition, text mining, and others. This paper aims to study the application in Chinese character recognition using non-negative matrix factorization. Python was used to carry out the LU factorization and non-negative matrix factorization of a Chinese character in Boolean Matrix. Preliminary analysis confirmed that the data size of and and are chosen for the NMF of the Boolean matrix. In this project, one hundred printed Chinese characters were selected, and all the Chinese characters can be categorized into ten categories according to the number of strokes , for . The Euclidean distance between the Boolean matrix of a Chinese character and the matrix after both LU factorization and NMF is calculated for further analysis. Paired t-test confirmed that the factorization of Chinese characters in the Boolean matrix using NMF is better than the LU factorization. Finally, ten handwritten Chinese characters were selected to test whether the program is able to identify the handwritten and the printed Chinese characters. Experimental results showed that 70% of the characters can be recognized via the least Euclidean distance obtained. NMF is suitable to be applied in Chinese character recognition since it can reduce the dimension of the image and the error between the original Boolean matrix and after NMF is less than 5%.
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Xiaolei, Jin. "THE NATURE OF THE CHINESE SCRIPT." Journal Human Research in Rehabilitation 9, no. 1 (April 2019): 99–101. http://dx.doi.org/10.21554/hrr.041912.
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This paper introduces the nature of the Chinese script, with the focus on its origin and development, the main four kinds of creation methods, the basic strokes of Chinese characters and the significance of its radical structure. The author believes that Chinese characters are the carriers of the script, phoneme and meaning as well as of the grammatical structure of the Chinese language. Hence, the Latin alphabet for the Chinese phonetic system cannot replace Chinese character, and learning Chinese character is very important for foreign learners. Finally, the author gives a mnemonic of the basic rules for stroke order that facilitates learners' memory and helps them write characters correctly and quickly.
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Dai, Zhenhua, and Jie Yang. "A Multimedia Learning for Chinese Character Image Recognition via Human-Computer Interaction Network." Advances in Multimedia 2022 (May 28, 2022): 1–7. http://dx.doi.org/10.1155/2022/4427091.
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As science and technology continue to develop, Chinese character image recognition technology is being used in a wide range of fields. This computer-based technology is a practical way of automatically recognizing images of text. Typically used in Chinese character education, it provides a new form of human–computer interaction for students. In addition, multimedia technology can provide a rich learning environment for students, which can present information about Chinese characters in the form of pictures, sounds, and videos, thus compensating for the disadvantages of learning Chinese characters by rote in the traditional educational process. The combination of Chinese character image recognition technology and multimedia technology can not only enrich the process of learning Chinese characters, but also promote students’ motivation to learn, thus providing a new and more modern approach to Chinese character education. Based on the study of Chinese character image recognition technology, this research combines it with multimedia information, to achieve the image recognition of Chinese character and multimedia information representation. The combined technology can provide significant references for course design and Chinese learners.
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Lee, Kweonhong. "A study on Chinese language acquisition method: “Chopping Chinese Characters” and “Chinese Character's Family”." Han-Character and Classical written language Education 2016, no. 41 (November 30, 2016): 49–69. http://dx.doi.org/10.15670/hace.2016.41.1.49.
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Chen, Zongze, Wenxia Yang, and Xin Li. "Stroke-Based Autoencoders: Self-Supervised Learners for Efficient Zero-Shot Chinese Character Recognition." Applied Sciences 13, no. 3 (January 30, 2023): 1750. http://dx.doi.org/10.3390/app13031750.
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Chinese characters carry a wealth of morphological and semantic information; therefore, zero-shot Chinese character recognition with the morphology of Chinese characters has drawn significant attention. The previous methods are mainly based on radical-level decomposition or stroke-level decomposition, which usually cannot capture adequately the structural and spatial information of Chinese characters. In this paper, we develop a stroke-based autoencoder (SAE), to model the sophisticated morphology of Chinese characters with a self-supervised method. Following its canonical writing order, we first represent a Chinese character as a series of stroke images with a fixed writing order, and then our SAE model is trained to reconstruct this stroke image sequence. This pre-trained SAE model can predict the stroke image series for unseen characters, as long as their strokes or radicals are in the training set. We have designed two contrasting SAE architectures on different forms of stroke images. One is fine-tuned on existing stroke-based method for zero-shot recognition of handwritten Chinese characters, and the other is applied to enrich the Chinese word embeddings from their morphological features. The experimental results validate that after pre-training, our SAE architecture outperforms other existing methods in zero-shot recognition and enhances the representation of Chinese characters with their abundant morphological and semantic information.
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Tseng, Yi-Hong, Chi-Chang Kuo, and Hsi-Jian Lee. "Typeface Identification for Printed Chinese Characters." International Journal of Pattern Recognition and Artificial Intelligence 12, no. 02 (March 1998): 173–90. http://dx.doi.org/10.1142/s0218001498000129.
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In this paper, we propose a methodology for identifying typefaces of printed Chinese characters in documents. Three kinds of features, stroke width means, stroke width variations, and aspect ratio, are first used to classify character typefaces as: Black, Li, Kai-Round, or Ming-Song. Each of the last two groups contains two typefaces. Vertical/horizontal stroke width ratios are used to distinguish between the Ming and Song typefaces and accumulative pixel ratio to distinguish between the Kai and Round typefaces. Six different typeface feature distributions measured from 5401 printed Chinese characters are considered, and a trapezoid-shaped membership function is constructed for each distribution. Based on these membership functions, we determine what typeface each input character belongs to using a two-level decision tree. To increase the identification rate, the typeface of a certain character is adjusted according to the typeface identification results of the front and the next characters. In the character recognition system, we use two statistical features: crossing counts and contour directional counts. We achieved an 89.87% typeface identification rate in our experiments, and a 95.60% character recognition rate.
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Yu, Lili, Qiaoming Zhang, Caspian Priest, Erik D. Reichle, and Heather Sheridan. "Character-complexity effects in Chinese reading and visual search: A comparison and theoretical implications." Quarterly Journal of Experimental Psychology 71, no. 1 (January 2018): 140–51. http://dx.doi.org/10.1080/17470218.2016.1272616.
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Three eye-movement experiments were conducted to examine how the complexity of characters in Chinese words (i.e., number of strokes per character) influences their processing and eye-movement behaviour. In Experiment 1, English speakers with no significant knowledge of Chinese searched for specific low-, medium-, and high-complexity target characters in a multi-page narrative containing characters of varying complexity (3–16 strokes). Fixation durations and skipping rates were influenced by the visual complexity of both the target characters and the characters being searched even though participants had no knowledge of Chinese. In Experiment 2, native Chinese speakers performed the same character-search task, and a similar pattern of results was observed. Finally, in Experiment 3, a second sample of native Chinese speakers read the same text used in Experiments 1 and 2, with text characters again exhibiting complexity effects. These results collectively suggest that character-complexity effects on eye movements may not be due to lexical processing per se but may instead reflect whatever visual processing is required to know whether or not a character corresponds to an episodically represented target. The theoretical implications of this for our understanding of normal reading are discussed.
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Zhu, Cheng Hui, Wen Jun Xu, Jian Ping Wang, and Xiao Bing Xu. "Research on a Characteristic Extraction Algorithm Based on Analog Space-Time Process for Off-Line Handwritten Chinese Characters." Advanced Materials Research 433-440 (January 2012): 3649–55. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.3649.
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On the absence of space-time information, it is difficult to extract the character stroke feature from the off-line handwritten Chinese character image. A feature extraction algorithm is proposed based on analog space-time process by the process neural network. The handwritten Chinese character image is transformed into geometric shape by different types, different numbers, different locations, different orders and different structures of Chinese character strokes. By extracting fault-tolerant features of the five kinds of the off-line handwritten Chinese characters, the data-knowledge table of features is constructed. The parameters of process neural networks are optimized by Particle Swarm optimization (PSO). The handwritten Chinese characters are used to carry out simulation experiment in SCUT-IRAC-HCCLIB. The experiment results show that the algorithm exhibits a strong ability of cognizing handwritten Chinese characters.
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Chen, Tianxu, and Yali Feng. "Nontransparent Compound Character Learning in L2 Chinese: Does Radical Awareness Always Work?" SAGE Open 10, no. 4 (October 2020): 215824402096966. http://dx.doi.org/10.1177/2158244020969669.
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Chinese character learning requires various reading subskills, such as radical awareness and character knowledge. Radical awareness refers to learners’ ability to identify, analyze, and apply semantic radicals in compound characters. Previous studies have shown that radical awareness and character knowledge facilitate learning semantically transparent characters. Yet, little is known regarding whether radical awareness plays an active role in the meaning retention for nontransparent characters. The meanings of transparent characters, such as “河” (river) containing the radical “氵” (water), are related to the semantic category of the radicals within the characters, whereas the meanings of nontransparent characters, such as “淑” (kind and gentle) with the same radical “氵,” are not directly related to the radicals. To fill these gaps, this study included 39 L2 Chinese learners at one American university. They completed one character-learning session, and five radical-related and character-related tasks. The results suggested that radical awareness did not positively affect the meaning retention for nontransparent characters when learners’ character knowledge was controlled. In addition, character knowledge was a moderator, which shaped the relationship between radical awareness and character retention. Pedagogical implications for the understanding of L2 Chinese compound character learning are discussed.
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Li, Te, Fang Yang, and Yao Song. "Visual Attention Adversarial Networks for Chinese Font Translation." Electronics 12, no. 6 (March 14, 2023): 1388. http://dx.doi.org/10.3390/electronics12061388.
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Currently, many Chinese font translation models adopt the method of dividing character components to improve the quality of generated font images. However, character components require a large amount of manual annotation to decompose characters and determine the composition of each character as input for training. In this paper, we establish a Chinese font translation model based on generative adversarial network without decomposition. First, we improve the method of image enhancement for Chinese character images. It helps the model learning structure information of Chinese character strokes to generate font images with complete and accurate strokes. Second, we propose a visual attention adversarial network. By using visual attention block, the network catches global and local features for constructing details of characters. Experiments demonstrate our method generates high-quality Chinese character images with great style diversity including calligraphy characters.
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Lin, Yao-San, Jie Ni Lim, and Yung-Sen Wu. "Developing and Applying a Chinese Character Learning Game App to Enhance Primary School Students’ Abilities in Identifying and Using Characters." Education Sciences 12, no. 3 (March 9, 2022): 189. http://dx.doi.org/10.3390/educsci12030189.
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The Chinese language is the mother tongue that most students in Singapore need to master. However, for many local students, due to the use of English as the main language in Singapore’s families and the living environment, the time and frequency of using Chinese and the exposure to Chinese characters are relatively insufficient, which leads to a high forgetting rate, confusion of the characters and the improper use of Chinese characters. This study attempts to develop an app of a Chinese character learning game for Singapore primary school students, aiming to stimulate students’ interest in learning Chinese, increase their frequency of contact and use of Chinese characters, and ultimately strengthen their ability to remember, understand and use Chinese characters. By collecting the data from students’ questionnaire surveys, teachers’ questionnaire surveys, students’ literacy tests, and classroom observations, the research team found that the designed app can enhance the interest of lower grade primary school students in learning Chinese and strengthen their ability to memorize and use Chinese characters.
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SUN, XINGMING, HUOWANG CHEN, LIHUA YANG, and Y. Y. TANG. "MATHEMATICAL REPRESENTATION OF A CHINESE CHARACTER AND ITS APPLICATIONS." International Journal of Pattern Recognition and Artificial Intelligence 16, no. 06 (September 2002): 735–47. http://dx.doi.org/10.1142/s0218001402001939.
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In this paper, a novel method to express Chinese characters mathematically is presented based on the knowledge of the structure of Chinese characters. Each Chinese character can be denoted by a mathematical expression in which the operands are components of Chinese characters and the operators are the location relations between the components. Five hundred five components are selected and 6 operators are defined to express all the Chinese characters successfully. These mathematical expressions of Chinese characters are simple, natural, and can be operated like the common mathematical expression of numbers. It makes Chinese information processing much simpler than before. This theory has been applied successfully in fonts automation, Chinese information transmission among different platforms and different operating systems on Internet, and knowledge discovery of the structure of Chinese characters. It can also be applied extensively to many areas such as typesetting, advertising, packing design, virtual library, network transmission, pattern recognition and Chinese mobile communication.
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TAN, JUN, XIAOHUA XIE, WEI-SHI ZHENG, and JIAN-HUANG LAI. "RADICAL EXTRACTION USING AFFINE SPARSE MATRIX FACTORIZATION FOR PRINTED CHINESE CHARACTERS RECOGNITION." International Journal of Pattern Recognition and Artificial Intelligence 26, no. 03 (May 2012): 1250005. http://dx.doi.org/10.1142/s021800141250005x.
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Each Chinese character is comprised of radicals, where a single character (compound character) contains one (or more than one) radicals. For human cognitive perspective, a Chinese character can be recognized by identifying its radicals and their spatial relationship. This human cognitive law may be followed in computer recognition. However, extracting Chinese character radicals automatically by computer is still an unsolved problem. In this paper, we propose using an improved sparse matrix factorization which integrates affine transformation, namely affine sparse matrix factorization (ASMF), for automatically extracting radicals from Chinese characters. Here the affine transformation is vitally important because it can address the poor-alignment problem of characters that may be caused by internal diversity of radicals and image segmentation. Consequently we develop a radical-based Chinese character recognition model. Because the number of radicals is much less than the number of Chinese characters, the radical-based recognition performs a far smaller category classification than the whole character-based recognition, resulting in a more robust recognition system. The experiments on standard Chinese character datasets show that the proposed method gets higher recognition rates than related Chinese character recognition methods.
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Cao, Wenjun, Julina Ismail@Kamal, and Chu Hiang Goh. "The Instructional Design of Chinese Characters’ Stroke Order Motion Graphics Based on Cognitive Load Theory." Malaysian Journal of Social Sciences and Humanities (MJSSH) 6, no. 10 (October 10, 2021): 469–79. http://dx.doi.org/10.47405/mjssh.v6i10.1108.
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This research aims to develop stroke order motion graphics for Chinese characters to solve the problem of memorising Chinese characters’ stroke order in the learning process. This research adopted cognitive load theory and the ADDIE model as an instructional design process guide. Herbart’s four-stage teaching method is used as a guide for the motion graphics presentation module. Based on the characteristics of Malaysian students who learn Chinese as their second language, motion graphics for Chinese characters’ stroke order learning were developed. The expert evaluation was conducted to identify problems, and modifications were done to improve the created prototype. A total of six Chinese characters’ stroke order motion graphics have been successfully developed. The result shows that cognitive load theory provides an effective solution for developing Chinese characters’ stroke order motion graphics. The ADDIE model also offered a significant direction for the instructional design process. In addition, to be more effective in Chinese character stroke order teaching, interface design must consider the relevant teaching effects of cognitive load theory. However, making the prototype in advance can avoid large-scale modifications in the later process. The successful development of the Chinese characters’ stroke order motion graphics allows teaching Chinese character stroke order in Malaysia to be carried out more effectively.
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Zhu, Lei, and Jing Yang. "Ancient Books Chinese Characters Segmentation Based on Connected Domain and Chinese Characters Feature." Advanced Materials Research 143-144 (October 2010): 227–31. http://dx.doi.org/10.4028/www.scientific.net/amr.143-144.227.
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During the processing of handwritten Chinese characters recognition, pretreatment and segmentation has great effect to the recognition. On the base of review upon the often-used algorithm, the article proposes the methods which get the connected domain of binary image use the non-recursion Marking algorithm, and design the algorithm to coherent noise and delete image frame line and segment the character. The article segment the character in the whole scope with the connected domain merging algorithm to overcame the difficult about the tilt; and segment the Chinese character in the part scope with the projection to overcome the difficult about conglutination. The fact proved that this algorithm solves the problem by using single method.
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Deng, Siqi, and Wenhua Hu. "An examination of Chinese character writing errors: Developmental differences among Chinese as a foreign language learners." Journal of Chinese Writing Systems 6, no. 1 (March 2022): 39–51. http://dx.doi.org/10.1177/25138502221066611.
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With interlanguage corpora, this study investigates the handwriting errors by Chinese as a foreign language (CFL) learners from eight countries and three language families (Indo-European languages, Slavic languages, Romance languages), including wrongly written characters and misused characters. The results indicate that the most common mistake among elementary, intermediate and advanced learners is wrongly written characters mainly caused by misuse of components, especially confusion between components and miswriting of components. Besides, stroke errors also matter. The reduction and improper location of strokes, in particular, trouble learners a great deal. As to the misused characters, how to differentiate similar characters is where the difficulties lie. On the whole, from the elementary stage to the intermediate stage, both types of errors decrease significantly, while after the intermediate stage, the decrease of wrongly written characters is more significant than that of the misused characters. Moreover, for advanced learners, the frequencies of these errors are basically the same. The study findings demonstrate that it is crucial for CFL learners to rapidly develop their awareness of orthography between the elementary and intermediate stages. This will last roughly 9 months. Advanced learners are usually well aware of orthography, but their awareness development of the form, pronunciation and meaning is not synchronized. They still make mistakes with details when writing. This research is instructive in the teaching of Chinese character handwriting. It points out the problems and countermeasures of online Chinese character handwriting courses during the pandemic and thus contributes advice to online Chinese character teaching during the long-term future.
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Liao, Ching-Chih. "Double-Sided Occluded Chinese Character Recognition Accuracy and Response Time for Design and Nondesign Educational Background." SAGE Open 8, no. 4 (October 2018): 215824401881006. http://dx.doi.org/10.1177/2158244018810065.
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This article investigates the influence of the position of occlusion, structural composition, and design educational status on Chinese character recognition accuracy and response time. Tsao and Liao conducted an experiment using 18 of the 4,000 most commonly used Chinese characters and suggested that the primary and secondary recognition features of a “single-sided” occluded Chinese character are the key radical (or initial strokes) and the key component (i.e., combination of strokes), respectively. The study concluded that right-side occluded characters require a shorter response time and yield more accurate recognition and that educational background does not significantly affect recognition accuracy and response time. The present study considered the same 18 Chinese characters and extended the work of Tsao and Liao by exploring accuracy rate and response time in design and nondesign educational groups for the recognition of “double-sided” occluded Chinese characters. The experimental results indicated that right-side occlusion (including both bottom-right and top-right occlusion) requires a shorter response time and yields more accurate recognition than left-side occlusion. These results agree with those of Tsao and Liao, who found that the key radical of a Chinese character is its key visual recognition feature. Even double-sided occlusion of Chinese characters does not affect the recognition outcome if the position of occlusion does not blur the key radical. Moreover, the participants majoring in design recognized the occluded Chinese characters more slowly than those with no educational background in design.
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Chao, Fei, Fuhai Chen, Yunhang Shen, Wenli He, Yan Sun, Zhengshuai Wang, Changle Zhou, and Min Jiang. "Robotic Free Writing of Chinese Characters via Human–Robot Interactions." International Journal of Humanoid Robotics 11, no. 01 (March 2014): 1450007. http://dx.doi.org/10.1142/s0219843614500078.
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Implementation of robotic writing ability is recognized as a difficult task, which involves complicated image processing and robotic control algorithms. This paper introduces a novel approach to robotic writing by using human–robot interactions. The method applies a motion sensing input device to capture a human demonstrator's arm trajectories, uses a gesture determination algorithm to extract a Chinese character's strokes from these trajectories, and employs noise filtering and curve fitting methods to optimize the strokes. The approach displays real-time captured trajectories to the human demonstrator; therefore, the human demonstrator is able to adjust his/her gesture to achieve a better character writing effect. Then, our robot writes the human-gestured character by using the robotic arm's joint values. The inverse kinematics algorithm generates the joint values from the stroke trajectories. Experimental analysis shows that the proposed approach can allow a human to naturally and conveniently control the robot in order to write many Chinese characters. Additionally, this approach allows the robot to achieve a satisfactory writing quality for characters with a simple structure, with the potential to write more complex characters.
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Young Hee You. "Learner's perception of Chinese characters and how to teach Chinese characters." Journal of Chinese Characters Education in Korea ll, no. 49 (December 2017): 155–85. http://dx.doi.org/10.17963/ccek.2017..49.155.
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Lee, Inkyung. "Ancient Chinese Cultural Ideas Reflected in Chinese Characters Associated with Wishes for Good Luck." Korean Society of Culture and Convergence 45, no. 11 (November 30, 2023): 1165–75. http://dx.doi.org/10.33645/cnc.2023.11.45.11.1165.
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This study was conducted by focusing on the fact that the Chinese character related to prayer for good luck in the radical '示' of “Shuowenjiezi(說文解字)” is not only the most distributed, but also placed at the very front. In this paper, we looked at ancient Chinese ancestral rite customs and cultural ideas reflected in ‘禮’ and ‘福’ before analyzing Chinese characters related to prayers for good fortune. Since '福' bestowed by the gods can only be achieved by avoiding '禍', this study conducted research by selecting 12 Chinese characters related to '福' and 8 Chinese characters related to '禍' as the Chinese characters related to blessings and blessings. Chinese characters related to wishes for good luck include '祿', '禠', '祥', '祉', '禎', '禧', '祺', '祗', '禛', '禔', It means God's protection, good omens and peace of life. ‘祈’ and ‘禱’ mean to pray for good fortune. In addition, the Chinese characters related to ‘禍’ include ‘禍’, ‘祟’, and ‘䄏’ to mean disaster imposed by God, ‘祓’, ‘’, ‘禜’, ‘禳’ and ‘禬’ to mean escape from disaster.
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Deng, Yuan, Tai-li Chou, Guo-sheng Ding, Dan-ling Peng, and James R. Booth. "The Involvement of Occipital and Inferior Frontal Cortex in the Phonological Learning of Chinese Characters." Journal of Cognitive Neuroscience 23, no. 8 (August 2011): 1998–2012. http://dx.doi.org/10.1162/jocn.2010.21571.
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Neural changes related to the learning of the pronunciation of Chinese characters in English speakers were examined using fMRI. We examined the item-specific learning effects for trained characters and the generalization of phonetic knowledge to novel transfer characters that shared a phonetic radical (part of a character that gives a clue to the whole character's pronunciation) with trained characters. Behavioral results showed that shared phonetic information improved performance for transfer characters. Neuroimaging results for trained characters over learning found increased activation in the right lingual gyrus, and greater activation enhancement in the left inferior frontal gyrus (Brodmann's area 44) was correlated with higher accuracy improvement. Moreover, greater activation for transfer characters in these two regions at the late stage of training was correlated with better knowledge of the phonetic radical in a delayed recall test. The current study suggests that the right lingual gyrus and the left inferior frontal gyrus are crucial for the learning of Chinese characters and the generalization of that knowledge to novel characters. Left inferior frontal gyrus is likely involved in phonological segmentation, whereas right lingual gyrus may subserve processing visual–orthographic information.
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Lee, Hahn-Ming, Chin-Chou Lin, and Jyh-Ming Chen. "A Preclassification Method for Handwritten Chinese Character Recognition Via Fuzzy Rules and Seart Neural Net." International Journal of Pattern Recognition and Artificial Intelligence 12, no. 06 (September 1998): 743–61. http://dx.doi.org/10.1142/s0218001498000427.
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In this paper, a method of character preclassification for handwritten Chinese character recognition is proposed. Since the number of Chinese characters is very large (at least 5401s for daily use), we employ two stages to reduce the candidates of an input character. In stage I, we extract the first set of primitive features from handwritten Chinese characters and use fuzzy rules to create four preclassification groups. The purpose in stage I is to reduce the candidates roughly. In stage II, we extract the second set of primitive features from handwritten Chinese characters and then use the Supervised Extended ART (SEART) as the classifier to generate preclassification classes for each preclassification group created in stage I. Since the number of characters in each preclassification class is smaller than that in the whole character set, the problem becomes simpler. In order to evaluate the proposed preclassification system, we use 605 Chinese character categories in the textbooks of elementary school as our training and testing data. The database used is HCCRBASE (provided by CCL, ITRI, Taiwan). In samples 1–100, we select the even samples as the training set, and the odd samples as the testing set. The characters of the testing set can be distributed into correct preclassification classes at a rate of 98.11%.
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Chen, Ju-Wei, and Suh-Yin Lee. "On-Line Chinese Character Recognition Via a Representation of Spatial Relationships Between Strokes." International Journal of Pattern Recognition and Artificial Intelligence 11, no. 03 (May 1997): 329–57. http://dx.doi.org/10.1142/s0218001497000159.
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Chinese characters are constructed by basic strokes based on structural rules. In handwritten characters, the shapes of the strokes may vary to some extent, but the spatial relations and geometric configurations of the strokes are usually maintained. Therefore these spatial relations and configurations could be regarded as invariant features and could be used in the recognition of handwritten Chinese characters. In this paper, we investigate the structural knowledge in Chinese characters and propose the stroke spatial relationship representation (SSRR) to describe Chinese characters. An On-Line Chinese Character Recognition (OLCCR) method using the SSRR is also presented. With SSRR, each character is processed and is represented by an attribute graph. The process of character recognition is thereby transformed into a graph matching problem. After careful analysis, the basic spatial relationship between strokes can be characterized into five classes. A bitwise representation is adopted in the design of the data structure to reduce storage requirements and to speed up character matching. The strategy of hierarchical search in the preclassification improves the recognition speed. Basically, the attribute graph model is a generalized character representation that provides a useful and convenient representation for newly added characters in an OLCCR system with automatic learning capability. The significance of the structural approach of character recognition using spatial relationships is analyzed and is proved by experiments. Realistic testing is provided to show the effectiveness of the proposed method.
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Ye, Qiuyue. "A Study on the Teaching of Chinese Characters in the Chinese Department of Eötvös Loránd University." Journal of Chinese Language Teaching in Europe 欧洲中文教育 1 (March 27, 2024): 29–41. http://dx.doi.org/10.61637/cltcee.2024.1.3.
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The teaching of Chinese characters is a “big problem” in teaching Chineseas a foreign language, especially for learners who are not in the cultural circle of Chinese characters, it is the biggest difficulty in learning process. This article analyzes the current situation of Chinese character teaching in the Chinese Department of Eötvös Loránd University from the aspects of teaching materials, teachers and teaching methods, points out the advantages and disadvantages, and proposes corresponding teaching strategies in order to improve the teaching effect of Chinese characters.
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Kim, Sangdeog Augustin. "Do you want me to be free from the state of my sadness? My Darling, my husband! You must reduce and reduce again your complain about me your wife (Tcheonzamun 305th-320th)." South Asian Research Journal of Humanities and Social Sciences 4, no. 4 (August 30, 2022): 305–7. http://dx.doi.org/10.36346/sarjhss.2022.v04i04.012.
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Dallet (1874) in his book introduced ‘Tcheonzamun (The thousand character essay)’, and he wrote that Tcheonzamun had been utilized for the children in the ancient Chinese people and in the ancient Korean people for the education of Chinese characters. The part of Tcheonzamun (The thousand character essay) here in this study was 16 letters of (Tcheonzamun 305th-320th). Two methods were used. The first method was through Korean pronunciation of Chinese character, and the second was through the meaning of the Chinese character of Tcheonzamun. In addition, the present researcher tried to delete same part from the two Chinese characters in the same line. And the remained parts of the Chinese character were utilized for the translation. (This is the translation through Korean pronunciation of Chinese characters) 317-320 去(Geo) 而(I) 益(Ig) 詠(Yeong) 꺼이 엉엉! Geoi Eong-eong (The wife cries by herself) I am sad, so I am crying! ‘Geoi Eong-eong’ is the crying voice of the wife. (This is the translation through the meaning of Chinese characters) 317-320 去(Keo) 而(I)-Ħ=一’ 益(Ig)-Ħ=小小 詠(Yeong). (The wife said to her husband). Do you want me to be free (去) from the state (一) of my sadness (’)? My Darling, my husband! You must reduce (小) and reduce again (小) your complain (詠) about me your wife.
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LU, YUE, and CHEW LIM TAN. "CHINESE WORD SEARCHING IN IMAGED DOCUMENTS." International Journal of Pattern Recognition and Artificial Intelligence 18, no. 02 (March 2004): 229–46. http://dx.doi.org/10.1142/s0218001404003137.
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An approach to searching for user-specified words in imaged Chinese documents, without the requirements of layout analysis and OCR processing of the entire documents, is proposed in this paper. A small number of Chinese characters that cannot be successfully bounded using connected component analysis due to larger gaps between elements within the characters are blacklisted. A suitable character that is not included in the blacklist is chosen from the user-specified word as the initial character to search for a matching candidate in the document. Once a matched candidate is found, the adjacent characters in the horizontal and vertical directions are examined for matching with other corresponding characters in the user-specified word, subject to the constraints of alignment (either horizontal or vertical direction) and size similarity. A weighted Hausdorff distance is proposed for the character matching. Experimental results show that the present method can effectively search the user-specified Chinese words from the document images with the format of either horizontal or vertical text lines, or both appearing on the same image.