Academic literature on the topic 'Chinese characters Pattern recognition systems. Optical character recognition devices'

Having received a lively response to our call for papers on the lexicography of Japanese as a second language, the editorial board decided to dedicate two issues of this year's ALA to this theme, and I am happy to introduce the second round of papers, after the first thematic issue published in October this year.This issue is again divided into two parts. The first two papers offer analyses of two aspects of existing dictionaries from the point of view of Japanese language learners, while the following four papers present particular lexicographic projects for learners of Japanese as a foreign language.The first paper, by Kanako Maebo, entitled A survey of register labelling in Japanese dictionaries - Towards the labelling of words in dictionaries for learners of Japanese, analyses register labelling in existing dictionaries of Japanese, both in those expressly intended for learners of Japanese as a second language and those intended for native speakers, pointing out how register information provided by such dictionaries is not sufficient for L2 language production. After stressing the usefulness of usage examples for learners trying to write in Japanese, she offers an example of a corpus-based register analysis and proposes a typology of labels to be assigned to dictionary entries, calling for the development of corpora of different genres to be used for lexical analysis.In the second paper, An analysis of the efficiency of existing kanji indexes and development of a coding-based index, Galina N. Vorobеva and Victor M. Vorobеv tackle one of the most time-consuming tasks learners of Japanese are confronted with: looking up unknown Chinese characters. After a comprehensive description of existing indexes, including less known indexing systems developed by Japanese, Chinese, Russian and German researchers, they compare the efficiency of these systems using the concept of selectivity, and propose their own coding-based system. Although searching for unknown characters is becoming increasingly easy with the use of optical character recognition included in portable electronic dictionaries, tablets and smart-phones, not all learners have yet access to such devices. Efficient indexes for accessing information on Chinese characters are therefore still a valuable tool to support language learners in this most tedious task, while the ability to decompose a character into component parts remains an important basis for character memorisation.The second part of this issue presents four projects aimed at supporting particular lexical needs of learners of Japanese as a second language.In the first paper, Development of a learners' dictionary of polysemous Japanese words and some proposals for learners’ lexicography, Shingo Imai presents a new lexicographic approach to the description of polysemous words. As Imai rightfully stresses, the most basic and common words learned by beginning language learners are actually often very polysemous; being deceivingly simple at first glance, they are often introduced with simple glosses or basic prototypical examples at the first stages of learning, and later treated as known words in intermediate or advanced textbooks, even if used for less common senses which are still unknown to the learners, causing much confusion. In the dictionary series presented here, polysemous headwords are thoroughly and systematically described within their semantic networks, where the connections between core and derived meanings are schematically visualised and exemplified.The following two papers present two of the first and most popular web-based systems for Japanese language learning support, both of which have been developing for more than a decade, supporting Japanese language learners all over the world.Reading Tutor, a reading support system for Japanese language learners, presented by Yoshiko Kawamura, is a widely known and used system based at Tokyo International University, which offers automatic glossing of Japanese text with Japanese definitions and examples, and translations into 28 languages. After introducing the system, its development, functionalities and its tools for signalling the level of difficulty of single words, characters, or whole Japanese texts, the author describes its possible uses in language instruction and autonomous learning, and one concrete example of its application to the development of learning material for a specific segment of learners, foreign candidates to the Japanese national examination for certified care workers, mostly Filipino and Indonesian nurses working in Japan. The author concludes with suggestions for fostering autonomous vocabulary learning.The other Japanese language learning support system with an equally long and successful tradition, developed at Tokyo Institute of Technology, is presented by its initiator, Kikuko Nishina, and one of its younger developers, Bor Hodošček, in Japanese Learning Support Systems: Hinoki Project Report. The article presents the many components of this successful system, including Asunaro, a reading support system aimed especially at science and engineering students and speakers of underrepresented Asian languages, Natsume, a writing assistance system using large-scale corpora to support collocation search, Natane, a learner corpus, and Nutmeg, an automatic error correction system for learners' writing.The last project report, by Tomaž Erjavec and myself, introduces resources and tools being developed at the University of Ljubljana and at Jožef Stefan Institute: JaSlo: Integration of a Japanese-Slovene Bilingual Dictionary with a Corpus Search System. The dictionary, corpora and search tools are being developed primarily for Slovene speaking learners of Japanese, but part of the tools, particularly the corpus of sentences from the web-harvested texts, divided into five difficulty levels, can be used by any learner or teacher of Japanese.I hope you will enjoy reading these articles as much as I did, and wish you a peaceful New Year.

From the Last twenty years, the computer-based mechanism has an essential process in daily life and research-oriented applications, the whole world be attracted by computers and approximately all the main processing is being completed automatically. Recognition of handwriting now it is an eye-catching and tough study analysis in image processing and pattern identification field in the today’s world. To beat this problem Optical Character Recognition system (OCR) is practice and concentrated research has been carrying on OCR. Numerous OCR systems are existing in the market other than mainly of this system working for Japanese, English, Chinese, Roman letters. There is no adequate work on Arabic language particularly Sheba characters. In proposed paper, an OCR system for Sheba recognition of character depend on neural network is presented. After analysing various method for segmentation and pre-processing A and B which are used for image pre-processing and segmentation respectively to enhance performance for projected framework. All the issues and challenges for OCR system and relevancy or accuracy of proposed method are discussed and analysed briefly