Recognition of Japanese handwritten characters with Machine learning techniques

The recognition of Japanese handwritten characters has always been a challenge for researchers. A large number of classes, their graphic complexity, and the existence of three different writing systems make this problem particularly difficult compared to Western writing. For decades, attempts have been made to address the problem using traditional OCR (Optical Character Recognition) techniques, with mixed results. With the recent popularization of machine learning techniques through neural networks, this research has been revitalized, bringing new approaches to the problem. These new results achieve performance levels comparable to human recognition. Furthermore, these new techniques have allowed collaboration with very different disciplines, such as the Humanities or East Asian studies, achieving advances in them that would not have been possible without this interdisciplinary work. In this thesis, these techniques are explored until reaching a sufficient level of understanding that allows us to carry out our own experiments, training neural network models with public datasets of Japanese characters. However, the scarcity of public datasets makes the task of researchers remarkably difficult. Our proposal to minimize this problem is the development of a web application that allows researchers to easily collect samples of Japanese characters through the collaboration of any user. Once the application is fully operational, the examples collected until that point will be used to create a new dataset in a specific format. Finally, we can use the new data to carry out comparative experiments with the previous neural network models

Semantic radical consistency and character transparency effects in Chinese: an ERP study

BACKGROUND: This event-related potential (ERP) study aims to investigate the representation and temporal dynamics of Chinese orthography-to-semantics mappings by simultaneously manipulating character transparency and semantic radical consistency. Character components, referred to as radicals, make up the building blocks used dur...postprin

Archives, Access and Artificial Intelligence

Digital archives are transforming the Humanities and the Sciences. Digitized collections of newspapers and books have pushed scholars to develop new, data-rich methods. Born-digital archives are now better preserved and managed thanks to the development of open-access and commercial software. Digital Humanities have moved from the fringe to the center of academia. Yet, the path from the appraisal of records to their analysis is far from smooth. This book explores crossovers between various disciplines to improve the discoverability, accessibility, and use of born-digital archives and other cultural assets

L2 Chinese Reading Comprehension among Beginning-Level, K-12 Learners: A Literature Review

This review focuses on beginning-level, K-12, L1 English learners, and considers their reading comprehension of texts written in Chinese characters and literacy development. Instructional approaches, materials design, and teaching and learning strategies related to reading texts in Chinese characters in these settings are reviewed. This review includes both empirical studies and think pieces that appeal to prior empirical work in L2 Chinese reading to understand what Chinese as a Second Language scholars research, discuss, and advocate about reading comprehension for L2 learners mainly at beginning levels of K-12 education. This literature review therefore includes a variety of source materials: empirical research, research-informed advocacy and think pieces, and action research studies by Chinese language instructors. The article concludes with observations about the state of research and current recommendations in Chinese as a second language reading comprehension