Dynamic Generation and Editing System for Wrongly Written Chinese Characters Font

The uniqueness of Chinese makes Chinese language a hotspot in language learning. In view of the problem of wrongly written character teaching in Chinese language teaching, it provides a simple, convenient, and efficient input method of wrongly written characters and realizes a dynamic generation and editing system for wrongly written Chinese character font, which solves the problems of real-time edit, coding, and input of wrongly written character in editing process using dynamic editing technology, and provides a convenient input method of wrongly written character in editing, printing, typesetting, and the research of digital Chinese language teaching. This method can also be used in dynamic editing, generation and processing of ancient variants, Oracle bone inscriptions, Bronze inscription, folk combined characters, and other fonts

Chinese in The Classroom: Initial Findings of The Effects of Four Teaching Methods on Beginner Learners

The following is an article documenting the researcher’s initial findings examining the effects of four different teaching methods on beginner CFL (Chinese as a foreign language) learners in terms of their ability to not only recall and recognize Chinese characters but also to use these characters for understanding and creating texts. The researcher is currently teaching approximately 98 students, aged 14-16, for one academic year. They are divided into four groups which each deploy a different teaching method. Depending on their groups, the participants are learning Chinese via rote memorization, delayed character introduction, character color-coding, and the method currently used in some Irish institutions, which focuses on the reading, writing, speaking and listening of Chinese as a whole. Therefore, participants in the fourth group are taught via integrated learning, without specific focus on the learning of characters as in the case of the other three groups. The outcomes of formative and summative evaluations throughout the year will highlight each group’s progression and therefore the effectiveness of each method, not only in terms of character recall and recognition, but also the use of the language. At the time of writing (November 2016), the researcher has completed approximately ten weeks of teaching (to continue until May 2017). This paper therefore presents a background to the study, a condensed literature review, methodology, preliminary findings and analysis of the first formative evaluation, and a summary of the project thus far, including correlations between theory and practice. So far, results from the first formative evaluation have suggested that the rote memorization group is the most successful in recalling and recognizing characters, whereas the character color-coding group has displayed positive results in terms of character use as well as character recall and recognition. The control group has shown strengths primarily in conducting exercises such as cloze tests and reordering sentences, and the delayed character introduction group has shown positive results in the use of and recognition of Chinese Pinyin, however it remains to be seen how this group will perform once the characters have been introduced. As the data collection will continue until the end of the academic year in May, further results of the remaining formative and summative evaluations will allow for more concrete correlations between teaching methods and learning outcomes to be established

The Phonological Process with Two Patterns of Simplified Chinese Characters

This paper analyzed word recognition in two patterns of Chinese characters, cross referenced with word frequency. The patterns were defined as uni-part (semantic radical/component only) and bi-part (including the phonetic radical/component and the semantic radical/component) characters. The interactions of semantic and phonological access in both patterns were inspected. It was observed that in the naming task and the pronunciation-matching task, the subject performance involving the uni-part characters showed longer RT than the bi-part characters. However, with the lexical decision and meaning-matching tasks the uni-part characters showed shorter RT than the bi-part characters. It was also observed that the frequency, which is regarded as a lexical variable, displayed a strong influence. This suggests that Chinese characters require lexical access in all tasks. This study also suggested that the phonological process is primary in visual word recognition; as there is a significant phonological effect in processing the Chinese bi-part characters, resulting in either the facilitation or inhibition of phonology due to the differing demands of the two task

Neural machine translation using bitmap fonts

Recently, translation systems based on neural networks are starting to compete with systems based on phrases. The systems which are based on neural networks use vectorial repre- sentations of words. However, one of the biggest challenges that machine translation still faces, is dealing with large vocabularies and morphologically rich languages. This work aims to adapt a neural machine translation system to translate from Chinese to Spanish, using as input different types of granularity: words, characters, bitmap fonts of Chinese characters or words. The fact of performing the interpretation of every character or word as a bitmap font allows for obtaining more informed vectorial representations. Best results are obtained when using the information of the word bitmap font.Postprint (published version

Six-Digit Stroke-based Chinese Input Method

Abstract-During the last three decades, more than one thousand Chinese input methods have been developed. However, people are still looking for better input methods in terms of easy to use, easy to remember, high input speed and small keypad implementation on handheld devices. The well-known strokebased Chinese input method using only five basic stroke types could achieve low learning curve and small numeric keypad implementation but its input speed is limited for complex Chinese characters with a lot of strokes. To tackle this problem, simplified stroke-based Chinese character and phrase coding methods using (3+3) rules are proposed in this paper. The proposed method only uses the first 3 stroke codes and the last 3 stroke codes to represent the first and last radical information of the character for achieving lower average code length and higher hit rate of first character on the candidate list. To further enhance the input speed, a very user-friendly (3+3) phrase coding rule is also proposed for inputting Chinese phrases in terms of 2-character, 3-character and long-character phrases. Three special key assignment designs are developed for practical implementation of the proposed Chinese character and phrase input method using conventional QWERTY keyboard, PC's numeric keypad and mobile phone 12-key keypad. Experimental results have shown that the proposed character coding can achieve lower average code length and higher Hit Rate of First Character as compared with conventional stroke-based method and some well-known Chinese input methods. The proposed coding rules are also very easy to use and remember

The effects of focused memorisation, delayed character introduction, character colour-coding, and a unity curriculum on the character learning of Beginner CFL learners

Teaching Chinese as a foreign language (henceforth CFL) has undoubtedly grown in popularity worldwide over the past number of years. CFL was first introduced as a module in Irish third-level institutions in the year 2006-2007, around the time when the first Confucius Institutes were founded in Ireland in University College Dublin and University College Cork. In 2014, a short course entitled ‘Chinese Language and Culture’ was introduced to the junior cycle of Irish secondary schools. It was compiled by the National Council for Curriculum and Assessment (NCCA) and provided a set of guidelines for teaching CFL from the beginner level. More recently, in 2017, it was announced that CFL would be introduced as a State-examined subject on the Leaving Certificate curriculum within 10 years. The following describes a quasi-experimental study with a focus on teaching Chinese characters to beginner learners in an Irish secondary school. Approximately 90 participants aged 14-16 years were divided into four groups, whereby each group was taught beginner-level Chinese under one teaching method of focused memorisation (FM), delayed character introduction (DCI), character colour-coding (CCC), or the unity curriculum (UC), which places equal focus on reading, writing, speaking, and listening. Participants were taught for one academic year, during which they conducted four formative evaluations – testing learning progress – and two summative evaluations – testing learning outcomes. These evaluations comprised exercises such as listening dictation, character recall and recognition, using characters in sentences, reordering sentences, and producing Chinese text. Findings from the current study show that a combined methodology of FM, CCC, and UC is possibly beneficial to beginner learners when learning character composition and how to use characters in a variety of contexts, while feedback from participants also demonstrated that the characters were one of the main difficulties in their learning of CFL. Evidence-based recommendations for a future CFL teaching methodology are therefore supplied in the current research, while recommendations for a CFL programme are also discussed

Applying MDL to Learning Best Model Granularity

The Minimum Description Length (MDL) principle is solidly based on a provably ideal method of inference using Kolmogorov complexity. We test how the theory behaves in practice on a general problem in model selection: that of learning the best model granularity. The performance of a model depends critically on the granularity, for example the choice of precision of the parameters. Too high precision generally involves modeling of accidental noise and too low precision may lead to confusion of models that should be distinguished. This precision is often determined ad hoc. In MDL the best model is the one that most compresses a two-part code of the data set: this embodies ``Occam's Razor.'' In two quite different experimental settings the theoretical value determined using MDL coincides with the best value found experimentally. In the first experiment the task is to recognize isolated handwritten characters in one subject's handwriting, irrespective of size and orientation. Based on a new modification of elastic matching, using multiple prototypes per character, the optimal prediction rate is predicted for the learned parameter (length of sampling interval) considered most likely by MDL, which is shown to coincide with the best value found experimentally. In the second experiment the task is to model a robot arm with two degrees of freedom using a three layer feed-forward neural network where we need to determine the number of nodes in the hidden layer giving best modeling performance. The optimal model (the one that extrapolizes best on unseen examples) is predicted for the number of nodes in the hidden layer considered most likely by MDL, which again is found to coincide with the best value found experimentally.Comment: LaTeX, 32 pages, 5 figures. Artificial Intelligence journal, To appea