A 4-Corner Codes Classifier Based on Decision Tree Inductive Learning for Handwritten Chinese Characters

The classification for handwritten Chinese character recognition can be viewed as a transformation in discrete vector space. In this paper, from the point of discrete vector space transformation, a new 4-corner codes classifier based on decision tree inductive learning algorithm ID3 for handwritten Chinese characters is presented. With a feature extraction controller, the classifier can reduce the number of extracted features and accelerate classification speed. Experimental results show that the 4-corner codes classifier performs well on both recognition accuracy and speed.

Translation of Four-Chinese-Character Structures——With the Report at the 19^(th) National Congress of the Communist Party of China as Case Study

Chinese is featured with four-Chinese-character structures.These forms are typical in pattern,sound and meaning delivery.The thesis,therefore,with classifications of the four-Chinese-character structures in the latest 19^(th)National Congress of the Communist Party of China,attempts to analyze translation methods such as literal translation and liberal translation as well as translation techniques such as combination,shift,addition and omission.It is concluded that dominant methods or techniques are adopted in translating corresponding types of four-Chinese-character structures.In this sense,not only guidance for translation practice in political regard is offered but also a further understanding of translation methods and techniques can be gained.

Basic Elements Knowledge Acquisition Study in the Chinese Character Intelligent Formation System

In the Chinese character intelligent formation system without Chinese character library, it is possible that the same basic element in different Chinese characters is different in position, size and shape. The geometry transformation from basic elements to the components of Chinese characters can be realized by affine transformation, the transformation knowledge acquisition is the premise of Chinese character intelligent formation. A novel algorithm is proposed to ac-quire the affine transformation knowledge of basic elements automatically in this paper. The interested region of Chi-nese character image is determined by the structure of the Chinese character. Scale invariant and location invariant of basic element and Chinese character image are extracted with SIFT features, the matching points of the two images are determined according to the principle of Minimum Euclidean distance of eigenvectors. Using corner points as identifi-cation features, calculating the one-way Hausdorff distance between corner points as the similarity measurement from the affine image to the Chinese character sub-image, affine coefficients are determined by optimal similarity. 70244 Chinese characters in National Standards GB18030-2005 character set are taken as the experimental object, all the characters are performed and the experimental courses and results are presented in this paper.

Development of Automatic Programming System for NC Laser Cutting of Chinese Characters

This Paper presents an automatic programming system developed for NC laser onning of Chinese charaCterswhich combines AutoCAD with NC Under Windows environment, and generates numerical controlled Programs by extracting outline (stroke) figures of Chinese Characters from outline character base, optimizing cutting routes, transferring them to AutoCAD for editing operations, such as rotation transfer, enlarging an mirroring, the system can transferto a laser cutting machine througy RS-232 series interface to accomplish laser cutting of large Chinese characters.

Structural recognition of ancient Chinese ideographic characters

Ancient Chinese characters, typically the ideographic characters on bones and bronze before Shang Dynasty(16th—11th century B.C.), are valuable culture legacy of history. However the recognition of Ancient Chinese characters has been the task of paleography experts for long. With the help of modern computer technique, everyone can expect to be able to recognize the characters and understand the ancient inscriptions. This research is aimed to help people recognize and understand those ancient Chinese characters by combining Chinese paleography theory and computer information processing technology. Based on the analysis of ancient character features, a method for structural character recognition is proposed. The important characteristics of strokes and basic components or radicals used in recognition are introduced in detail. A system was implemented based on above method to show the effectiveness of the method.

Data Pre－processing and Stroke Segment Extraction for On－line Handwritten Chinese Character Recognition

The stroke segments:' are proposed to be used as the basic features for handwritten Chinese character recognition. In this way, it is possible to overcome the difFiculties of unstable stroke information caused by stroke Joinings. The techniques of data pre-processing and stroke segment extraction have been described. In extracting stroke segment, not only the characteristics of the stroke itself, but also its absolute positions as well as relative positions with other strokes in the character have been taken into account.The primitive features for recognition were extracted under these comprehensive considerations.

A Study on the Effect of Creative Chinese Characters Learning on the Ability to Learn Chinese Old Sayings and Idioms Using K-Pop Music Video

Music is an extraordinary bridge between people all over the world so much as to be called a universal language. Idols and B-boys stages are fun, touching, and fantastic. Today, South Korean students are excited and enthusiastic about their colorful dance moves. The study is about creative educational methods that use K-pop music videos to learn the proverbs and old words that our ancestors learned to keep in mind and teach. K-pop lyrics are a rich reflection of the experiences of life and the world in which people are living today. Accordingly, this study can present new teaching and learning method examples that are used in class related to the old language associated with K-pop lyrics and can also introduce interesting class materials.

A Comparative Analysis of the Origin and Formation Between Chinese Characters and English Alphabets

This research is based on the framework of social constructivism,utilizing the principle of Human Universals as a methodology to compare the similarities and differences between the ideation and formation methods of Chinese characters and English alphabets.Through comparative analysis of the ideation of English letters(pictogramme)and the origin of Chinese characters,known as the"Six Categories Theory,"we discover their alignment in terms of social,traditional,and cultural aspects.This suggests that different ethnic groups share common features in terms of life experience,learning cognitive development,and thinking habits.This study also finds that the origins of English letters and Chinese characters share similar linguistic features in their methods of constructing letters/characters,such as pictographic,ideographic,and semantic characteristics.Exploring these commonalities contributes to promoting learning and communication between Chinese and English characters.Additionally,by focusing on socio-cultural aspects,traditional customs,and cognitive learning,this study aims to break away from the traditional linguistic research approach that solely focuses on language differences.This provides a broader perspective and richer dimensions for Chinese and English language learning,facilitating the development of cross-linguistic and cross-cultural communication.

A Review of Research on Handwritten Chinese Character Recognition with Multi-Feature Fusion

This paper analyzes the progress of handwritten Chinese character recognition technology,from two perspectives:traditional recognition methods and deep learning-based recognition methods.Firstly,the complexity of Chinese character recognition is pointed out,including its numerous categories,complex structure,and the problem of similar characters,especially the variability of handwritten Chinese characters.Subsequently,recognition methods based on feature optimization,model optimization,and fusion techniques are highlighted.The fusion studies between feature optimization and model improvement are further explored,and these studies further enhance the recognition effect through complementary advantages.Finally,the article summarizes the current challenges of Chinese character recognition technology,including accuracy improvement,model complexity,and real-time problems,and looks forward to future research directions.

The Spread of Chinese-character Culture on the Silk Road During the Tang Dynasty

The spread of Chinese characters and Chinese classic works during the Tang Dynasty presented diversified discourses of acceptance and development in different periods and regions. This was due to the differences in commercial, economic, political, religious, and cultural environments proportional to the real environment's demand for Chinese characters and Chinese classical works. Chinese characters were introduced to Gaochang, Qiuci, Khotan, Korea, Japan, and Vietnam as early as the Han Dynasty, with different development paths in these regions. It is easy to form a long lasting culture spread by Chinese language and characters, as long as official languages are consistent with national or religious languages of the regions. It is difficult to form a long lasting culture spread by official languages and characters if the official languages and characters are inconsistent with either languages of daily life or religious languages. Once there is replacement of official languages and characters, or a change in religious belief, it would cause incompatibility between official languages and daily life languages, Chinese-character culture is bound to decline and gradually fade way. But if there are Han people, they will retain the use of Chinese characters.

An exemplification of the Evolving Process by Studying the Chinese Character Mao

This paper tries to demarcate the evolving process of decategorization into three periods and exemplify it by studying the Chinese character Mao.The exemplification shows the correctness of the demarcation.

A Study on the Traditional Chinese Traditional Architectural Form of Mythological Tradition

Objective Through the metaphorical archetypal spirit and mythological semantics of Chinese character structure, this paper explores the metaphorical mythological gene and the moral order of the Chinese character structure, geographical thinking and aesthetic orientation of the mythological prototypes derived from the Chinese characters. Method The cultural archetypes and the theories of big and small traditions are adopted to sort out the mythological beliefs in the former architectural forms of the big traditions and the ethical narrative system carried by the buildings in the small cultural traditional societies. In the architectural archetypes dominated by big and small cultural traditions, the thinking of “archetypes and ethics” is found to be a homologous gene, which confirms the universal significance of the spirit of Chinese Confucian ethics to the power of Chinese civilization flowing and inheriting and human morality. Conclusion The structure of Chinese characters has the function of “recording” and “interpreting”, and the mythological thinking of architectural form materials, understands the ultimate transformation of cultural archetypes in creation, and guides the value of the traditional architectural design of “bringing out goodness and symbiosis” in the contemporary era. To relieve the material pursuit of spiritual enjoyment at that moment, to promote cultural heritage and the role of social treatment, to build cultural identity and the spiritual transcendence of the existence value of space ethics and the overall social and cultural identity.

Incorporating Linguistic Rules in Statistical Chinese Language Model for Pinyin-to-character Conversion

An N-gram Chinese language model incorporating linguistic rules is presented. By constructing elements lattice, rules information is incorporated in statistical frame. To facilitate the hybrid modeling, novel methods such as MI-based rule evaluating, weighted rule quantification and element-based n-gram probability approximation are presented. Dynamic Viterbi algorithm is adopted to search the best path in lattice. To strengthen the model, transformation-based error-driven rules learning is adopted. Applying proposed model to Chinese Pinyin-to-character conversion, high performance has been achieved in accuracy, flexibility and robustness simultaneously. Tests show correct rate achieves 94.81% instead of 90.53% using bi-gram Markov model alone. Many long-distance dependency and recursion in language can be processed effectively.

Use of Chineses 4-character Expressions

The use of Chinese 4character phrasesis dealt with. The possible ways of the use of Chinese 4character phrases are offered and some of the factors to be considered have been pointed out.

Discussion of Online Teaching Strategies for Teaching Elementary Chinese Characters to Foreigners Based on Error Analyses

The expanding role of the Chinese language in international communications has become increasingly prominent as China’s comprehensive national power continues to grow,leading to a significant rise in the number of Chinese language learners.Since online teaching is not limited by time and space,its application is widespread.For beginners in the Chinese language,the Chinese characters are both a priority and a challenge.The“Chinese Character Classification,”also known as the“Six Writings,”is the earliest systematic theory of Chinese character structures,and teaching Chinese characters in categories based on the“Chinese Character Classification”is a method that fits the cognition of beginners.In order to teach Chinese characters in a targeted approach,based on the collection and analysis of the common errors of Chinese characters among beginners,(1)this paper proposes that(a)the intuitive method can be applied to teach pictographic characters,indicative characters,and associative compound characters in online teaching;(b)the inductive-deductive method of“basic characters to new characters”can be applied for the teaching of pictophonetic characters and associative compound characters;(c)the learning of character patterns should be approached in a whole-part-whole process,while importance should be attached to the suggestion of the frequency effect with a view to facilitating the online learning of Chinese characters for beginners.The aim of this paper is to provide some practical implications for the online teaching of Chinese characters to foreigners.

The Research on Character Design Based on the Chinese Mythology:A Case Study of Shisa

Chinese mythology with its profound cultural asserts and the unconstrained imagination is an indispensable factor in animation creation.The rich resources of myth in ancient China provided a broad space for the creation of animation film and inherited a long ethnic culture.Firstly,the study creates an animation mythological character design model according to the literature review to provide the operational theory for animation design,which consists of three main parts:central idea,research method,and conceptual model.Secondly,the research sums up the animation character creative process framework through the case of Shisa with the specific ideas of creative design.Four steps are used to design a mythological character:set a scenario(illustration),tell a story(interpretation),write a script(reaction),and design a character(reflection).It has analyzed how to integrate the information about the mythology and stimulate the designers’creative imagination in the animation character design in order to create the artworks with unique oriental charm.

A New Method for Chinese Character Strokes Recognition

In this paper, the problem of stroke recognition has been studied, and the strategies and the algorithms related to the problem are proposed or developed. Based on studying some current methods for Chinese characters strokes recognition, a new method called combining trial is presented. The analysis and results of experiments showed that the method has the advantage of high degree of steadiness.

Using Neuroeducation as a Model to Evaluate the Effect of Imagery on Chinese Character Writing

Using imagery as a strategy for language learning may be helpful to encode linguistic forms into conceptual networks for long-term memory. Based on Arwood＇s neuroeducation model of language learning, this research evaluated the effect of imagery in Chinese character writing by English-speaking adolescent students. After comparing imagery effects under three instructional conditions （i.e., English translation, pictorial presentation, and verbal-contextual interpretation）, the results showed that the use of imagery predicted significantly better writing results in the immediate and one-week writing tests, but not in the four-week writing test. Cognitive analyses found that imagery was commonly used as a mediational strategy in the pictorial and verbal-contextual methods in the early learning phases. The pictorial method mainly elicited perceptual visual patterns which failed to support sustained memory. For a better character encoding and retrieval, images had to be generated associated with sufficient and relevant contextual information.

Typos Correction in Overseas Chinese Learning Based on Chinese Character Semantic Knowledge Graph

In recent years, more and more foreigners begin to learn Chinese characters, but they often make typos when using Chinese. The fundamental reason is that they mainly learn Chinese characters from the glyph and pronunciation, but do not master the semantics of Chinese characters. If they can understand the meaning of Chinese characters and form knowledge groups of the characters with relevant meanings, it can effectively improve learning efficiency. We achieve this goal by building a Chinese character semantic knowledge graph (CCSKG). In the process of building the knowledge graph, the semantic computing capacity of HowNet was utilized, and 104,187 associated edges were finally established for 6752 Chinese characters. Thanks to the development of deep learning, OpenHowNet releases the core data of HowNet and provides useful APIs for calculating the similarity between two words based on sememes. Therefore our method combines the advantages of data-driven and knowledge-driven. The proposed method treats Chinese sentences as subgraphs of the CCSKG and uses graph algorithms to correct Chinese typos and achieve good results. The experimental results show that compared with keras-bert and pycorrector + ernie, our method reduces the false acceptance rate by 38.28% and improves the recall rate by 40.91% in the field of learning Chinese as a foreign language. The CCSKG can help to promote Chinese overseas communication and international education.