Hasil untuk "Japanese language and literature"

Gayathri Haththotuwa Gamage

Linda Unsriana, Bosya Perdana, Sunda Ariana et al.

The emergence of Industry 4.0 has significantly transformed higher education by promoting the integration of smart learning technologies across various disciplines. However, the adoption of digital tools in the humanities, particularly in Japanese literature education, remains limited due to perceived incompatibilities between technological interfaces and the cultural and aesthetic intricacies of literary study. This research investigates the efficacy and challenges of implementing gamified and AI-powered learning systems within Japanese litrary curricula. Utilizing a qualitative case study approach, data were collected through interviews with instructors and students, observations of Learning Management Systems, and analysis of digital course materials across multiple universities. Thematic analysis combined with Kirkpatrick’s four-level evaluation model revealed that digital tools, including natural language processing-based text analysis and adaptive learning frameworks, improved student engagement, cultural comprehension, and instructional flexibility. Gamified elements such as badge systems and interactive timelines enhanced motivation and increased completion rates for supplemental modules. Despite these benefits, the study identified persistent barriers related to infrastructure disparities, limited educator training, and difficulties in conveying literary aesthetics such as yūgen through digital platforms. The findings underscore the potential of smart learning systems to enrich literary education when supported by pedagogically informed design and institutional commitment. This study addresses a significant gap in the digital humanities literature by exploring the intersection of artificial intelligence, gamification, and non-Western literary instruction. Future research should develop hybrid learning models that combine traditional and digital methods, and apply longitudinal assessments to evaluate sustained educational impact.

Ina Hein

The dominant notion that modern Japanese literature is a national literature – written (only) by ethnic Japanese, whose mother tongue is Japanese, in the Japanese language, for a Japanese reading audience – is recently challenged by writers who are non-native speakers of Japanese, having been born and raised outside of Japan, and, after having migrated to Japan, deliberately chose Japanese as their literary language, thus becoming authors of literature in Japanese. This article shows how these writers decenter the Japanese language, Japanese literature, and ultimately ‘Japaneseness’ as such – on the plot-level of their texts as well as by stylistic and linguistic means. I argue that this kind of literature aims at de-nationalizing the understanding of ‘Japanese literature’, and in that sense can and should be read as new world literature.

V. A. Bushmakin, V. P. Zaytsev

This article examines and analyzes the report of the Tokyo Geographical Society correspondent Kambe Ōichi, entitled “Records of Things Heard on Vladivostok” (Kaisan’i kibun 海參威記聞 = 海參崴 紀聞). It was published in 1882–1883. For the first time, detailed historiographical and bibliographic information about it is provided, the history of its publication is traced, and its contents are revealed. The report consists of three parts – records for the period from May 1881 to April 1882, an appendix to them in the form of an “annual report” of the Vladivostok city government for 1882, and a continuation of records covering the period from April 1882 to May 1883. The report was written at a time when representative offices of Japanese companies were just beginning to open in Vladivostok, which naturally led to the expansion of the Japanese presence and diaspora in the region, and therefore it provides invaluable historical information about this early stage of the penetration of Japanese business into the Russian Far East. Despite its importance, this source is now largely forgotten. This publication is an attempt to point out its importance and reintroduce it into scientific circulation. We believe that this will make a significant contribution to research on the history of Vladivostok and Primorsky Krai in all its aspects and will help to supplement the information available in Russian-language sources. This article is only the first step in studying Kambe’s report. Much work remains to be done to decipher the names found there, as well as to identify the primary sources – the Russian and English documents that Kambe had at his disposal and that formed the basis of his translations.

M. R. Alekseenko

The article is devoted to revealing the mechanisms of depicting the process of identity transformation in the literary work of the Japanese diaspora in Brazil. The aim is achieved by studying small prose in the genre of naturalism using the material of the Collection of Colonia Stories. The time frame is limited by the arrival of immigrants in 1908 and the prohibition of foreign language printing in 1941.The article describes the formation of the collective identity of the Japanese in Brazil from a historical perspective. The key features of the Japanese emigration, further reflected in the literary work of the diaspora in Brazil, are revealed: regional localization, migrants’ belonging to the peasantry, the formation of a special koroniago dialect. Special attention is paid to the reasons for the split within the diaspora, which became the main motif in the problems of literary works. Intragroup disunity has its roots in the social structure of the Japanese community and was stimulated by the urbanization of the 1930s.The article analyzes the process of formation of a distinctive center of literary creativity in the Japanese emigration in Brazil. The mechanisms of alienation of literary works based on the opposition between “pure” and “mass” literature are revealed.The transformation of Japanese identity in Brazil is evidenced by analyzing the problematics of the works. The painful process of integration into the host community gives center stage to the racial-ethnic issues of imin bungaku. The works depict the interaction between Japanese and Brazilians through inter-ethnic conflicts. The works studied reflect discursive patterns of describing the racial Other in the space of literature. The works are particularly sensitive to the betrayal of intra-community bonds and the acquisition of the traits of the host community. The process of identity transformation is examined in literature through the prism of social status, ethnicity, and gender discrimination. The analysis of the works shows the evolution of the representation of the Other from demonization and rejection to acceptance of the transformed identity. The change of perspective on the formation of a bicultural “Japanese-Brazilian” identity on the eve of World War II was interrupted by the outburst of Japanese nationalism during the war years. However, the acceptance of one’s own otherness and the literary representation of this process would become the foundation for the successful integration of the Japanese into Brazilian society in the postwar decades.

Keito Sasagawa, Shuhei Kurita, Daisuke Kawahara

Multimodal Large Language Models (MLLMs) have seen rapid advances in recent years and are now being applied to visual document understanding tasks. They are expected to process a wide range of document images across languages, including Japanese. Understanding documents from images requires models to read what are written in them. Since some Japanese documents are written vertically, support for vertical writing is essential. However, research specifically focused on vertically written Japanese text remains limited. In this study, we evaluate the reading capability of existing MLLMs on vertically written Japanese text. First, we generate a synthetic Japanese OCR dataset by rendering Japanese texts into images, and use it for both model fine-tuning and evaluation. This dataset includes Japanese text in both horizontal and vertical writing. We also create an evaluation dataset sourced from the real-world document images containing vertically written Japanese text. Using these datasets, we demonstrate that the existing MLLMs perform worse on vertically written Japanese text than on horizontally written Japanese text. Furthermore, we show that training MLLMs on our synthesized Japanese OCR dataset results in improving the performance of models that previously could not handle vertical writing. The datasets and code are publicly available https://github.com/llm-jp/eval_vertical_ja.

Ju-Young Kim, Ji-Hong Park, Se-Yeon Lee et al.

Recent incidents in certain online games and communities, where anonymity is guaranteed, show that unchecked inappropriate remarks frequently escalate into verbal abuse and even criminal behavior, raising significant social concerns. Consequently, there is a growing need for research on techniques that can detect inappropriate utterances within conversational texts to help build a safer communication environment. Although large-scale language models trained on Korean corpora and chain-of-thought reasoning have recently gained attention, research applying these approaches to inappropriate utterance detection remains limited. In this study, we propose a soft inductive bias approach that explicitly defines reasoning perspectives to guide the inference process, thereby promoting rational decision-making and preventing errors that may arise during reasoning. We fine-tune a Korean large language model using the proposed method and conduct both quantitative performance comparisons and qualitative evaluations across different training strategies. Experimental results show that the Kanana-1.5 model achieves an average accuracy of 87.0046, improving by approximately 3.89 percent over standard supervised learning. These findings indicate that the proposed method goes beyond simple knowledge imitation by large language models and enables more precise and consistent judgments through constrained reasoning perspectives, demonstrating its effectiveness for inappropriate utterance detection.

K. E. K. Adnyani, Putu Dewi Merlyna Yuda Pramesti, G. Hermawan

Diminutives play a significant role in communication directed toward infants and children, serving both linguistic and social functions. However, studies that specifically and comprehensively examine diminutives in the Japanese language remain limited. This literature review aims to describe the morphological forms and semantic meanings of Japanese diminutives based on previous research. The study adopts a qualitative descriptive approach using a narrative literature review method. In Japanese, diminutives appear in various grammatical forms, including honorific name suffixes (e.g., -chan), performative honorifics (e.g., -dechu), nouns (e.g., uchagi), adjectives (e.g., kuchai), adverbs (e.g., chukochi), verbs (e.g., achobu), and adpositional forms (e.g., chochite). The meanings of these diminutives are context-dependent and can be interpreted within the conceptual framework proposed by Schneider, encompassing notions such as smallness, affection, and sweetness. By synthesizing existing studies, this review contributes to a deeper understanding of the morphopragmatic and sociolinguistic functions of diminutives in Japanese. It also highlights the need for further research to explore their broader communicative and cultural significance in everyday interaction.

Nina Cornyetz

As translated Japanese literature crosses over to become world literature, there still are Orientalist assumptions about modern Japanese literature across the global academy at large, as of limited scope, rejecting fictionalization, and exploring states of mind. The objective of this essay is to counter essentialist and dated assumptions about modern Japanese literature by highlighting the actual breadth and diversity of English translations that negate these stereotypes. I even question postulating any homogeneous genre under the rubric “Japanese literature.” I begin with a broad survey of English-language reviews by non-area-specialists of three contemporary texts of Japanese literature in translation: Mizumura Minae’s  (b. 1951) A True Novel (Honkaku shōsetsu, 2002), Kirino Natsuo’s (b. 1951) OUT (AUTO, 1997), and Kaneshiro Kazuki’s (b. 1968) Go (Gō, 2000).  I follow that survey by revisiting and putting into question the dominant literary discourse by Japan specialists regarding just what constitutes “modernity” in Japanese literary studies. I then return my focus to the three contemporary Japanese novels already introduced. In the following order I will take up the complexities of each of the three novels’ plots, narration strategies, focalization, issues of ethnicity and race, relation of the individual to social conflicts and issues, and degrees of fictionalization versus realism. Finally, I will show how these various aspects of each of the three can moreover be seen as complementary to some of the most highly regarded fictions of the belle lettres traditions of Japanese modern literature, and hence belong in an alternative genealogy of modern Japanese literature.

S. Tan, S. L. Goei, T. Willemse

Via Luviana Dewanty, Nuria Haristiani, Leo Sadewo et al.

The integration of technology into language learning has led to increased research on the use of technology and media in language learning in recent years. This study presents a bibliometric analysis of the scientific literature related to the use of Technology and Media in Japanese Language Learning. Bibliometric methods are used in the analysis of scientific articles indexed on the Google Scholar database from 2018-2023, and linked to the research areas of Technology/Media in Japanese Language Learning. The research results show that the number of publications related to technology and media in Japanese language learning has increased in recent years. As the results of this research, publication related to technology and media in Japanese language learning is a growing trend that will lead to more research in the coming years. This study identifies opportunities for future research and pedagogical advances in Japanese language learning. Thus, it can become a source of information about innovation research in Japanese language learning.

Jian Cui

: This article explores the current situation and challenges of Japanese language teaching and learning in the era of new media. Through in-depth analysis of the application of new media tools in Japanese language teaching, the article proposes a series of strategies and methods to enhance the effectiveness of Japanese language learning. The research finds that Japanese language teaching in the new media era needs to pay more attention to students' diverse needs and learning habits, utilizing advanced technological means to provide students with a more enriching and flexible learning experience. Combining examples, the article elaborates on how to better integrate online platforms, social media, and other resources to promote the depth and expansion of Japanese language learning.

Leonidas Gee, Andrea Zugarini, Novi Quadrianto

To reduce the inference cost of large language models, model compression is increasingly used to create smaller scalable models. However, little is known about their robustness to minority subgroups defined by the labels and attributes of a dataset. In this paper, we investigate the effects of 18 different compression methods and settings on the subgroup robustness of BERT language models. We show that worst-group performance does not depend on model size alone, but also on the compression method used. Additionally, we find that model compression does not always worsen the performance on minority subgroups. Altogether, our analysis serves to further research into the subgroup robustness of model compression.

Yuichi Inoue, Kento Sasaki, Yuma Ochi et al.

Vision Language Models (VLMs) have undergone a rapid evolution, giving rise to significant advancements in the realm of multimodal understanding tasks. However, the majority of these models are trained and evaluated on English-centric datasets, leaving a gap in the development and evaluation of VLMs for other languages, such as Japanese. This gap can be attributed to the lack of methodologies for constructing VLMs and the absence of benchmarks to accurately measure their performance. To address this issue, we introduce a novel benchmark, Japanese Heron-Bench, for evaluating Japanese capabilities of VLMs. The Japanese Heron-Bench consists of a variety of imagequestion answer pairs tailored to the Japanese context. Additionally, we present a baseline Japanese VLM that has been trained with Japanese visual instruction tuning datasets. Our Heron-Bench reveals the strengths and limitations of the proposed VLM across various ability dimensions. Furthermore, we clarify the capability gap between strong closed models like GPT-4V and the baseline model, providing valuable insights for future research in this domain. We release the benchmark dataset and training code to facilitate further developments in Japanese VLM research.

Yanis Labrak, Adrien Bazoge, Beatrice Daille et al.

Subword tokenization has become the prevailing standard in the field of natural language processing (NLP) over recent years, primarily due to the widespread utilization of pre-trained language models. This shift began with Byte-Pair Encoding (BPE) and was later followed by the adoption of SentencePiece and WordPiece. While subword tokenization consistently outperforms character and word-level tokenization, the precise factors contributing to its success remain unclear. Key aspects such as the optimal segmentation granularity for diverse tasks and languages, the influence of data sources on tokenizers, and the role of morphological information in Indo-European languages remain insufficiently explored. This is particularly pertinent for biomedical terminology, characterized by specific rules governing morpheme combinations. Despite the agglutinative nature of biomedical terminology, existing language models do not explicitly incorporate this knowledge, leading to inconsistent tokenization strategies for common terms. In this paper, we seek to delve into the complexities of subword tokenization in French biomedical domain across a variety of NLP tasks and pinpoint areas where further enhancements can be made. We analyze classical tokenization algorithms, including BPE and SentencePiece, and introduce an original tokenization strategy that integrates morpheme-enriched word segmentation into existing tokenization methods.

Phillip Richter-Pechanski, Philipp Wiesenbach, Dominic M. Schwab et al.

Automatic extraction of medical information from clinical documents poses several challenges: high costs of required clinical expertise, limited interpretability of model predictions, restricted computational resources and privacy regulations. Recent advances in domain-adaptation and prompting methods showed promising results with minimal training data using lightweight masked language models, which are suited for well-established interpretability methods. We are first to present a systematic evaluation of these methods in a low-resource setting, by performing multi-class section classification on German doctor's letters. We conduct extensive class-wise evaluations supported by Shapley values, to validate the quality of our small training data set and to ensure the interpretability of model predictions. We demonstrate that a lightweight, domain-adapted pretrained model, prompted with just 20 shots, outperforms a traditional classification model by 30.5% accuracy. Our results serve as a process-oriented guideline for clinical information extraction projects working with low-resource.

Keito Sasagawa, Koki Maeda, Issa Sugiura et al.

To develop high-performing Visual Language Models (VLMs), it is essential to prepare multimodal resources, such as image-text pairs, interleaved data, and instruction data. While multimodal resources for English are abundant, there is a significant lack of corresponding resources for non-English languages, such as Japanese. To address this problem, we take Japanese as a non-English language and propose a method for rapidly creating Japanese multimodal datasets from scratch. We collect Japanese image-text pairs and interleaved data from web archives and generate Japanese instruction data directly from images using an existing VLM. Our experimental results show that a VLM trained on these native datasets outperforms those relying on machine-translated content.

Kai-Wei Chang, Haibin Wu, Yu-Kai Wang et al.

Prompting has become a practical method for utilizing pre-trained language models (LMs). This approach offers several advantages. It allows an LM to adapt to new tasks with minimal training and parameter updates, thus achieving efficiency in both storage and computation. Additionally, prompting modifies only the LM's inputs and harnesses the generative capabilities of language models to address various downstream tasks in a unified manner. This significantly reduces the need for human labor in designing task-specific models. These advantages become even more evident as the number of tasks served by the LM scales up. Motivated by the strengths of prompting, we are the first to explore the potential of prompting speech LMs in the domain of speech processing. Recently, there has been a growing interest in converting speech into discrete units for language modeling. Our pioneer research demonstrates that these quantized speech units are highly versatile within our unified prompting framework. Not only can they serve as class labels, but they also contain rich phonetic information that can be re-synthesized back into speech signals for speech generation tasks. Specifically, we reformulate speech processing tasks into speech-to-unit generation tasks. As a result, we can seamlessly integrate tasks such as speech classification, sequence generation, and speech generation within a single, unified prompting framework. The experiment results show that the prompting method can achieve competitive performance compared to the strong fine-tuning method based on self-supervised learning models with a similar number of trainable parameters. The prompting method also shows promising results in the few-shot setting. Moreover, with the advanced speech LMs coming into the stage, the proposed prompting framework attains great potential.

Kei Sawada, Tianyu Zhao, Makoto Shing et al.

AI democratization aims to create a world in which the average person can utilize AI techniques. To achieve this goal, numerous research institutes have attempted to make their results accessible to the public. In particular, large pre-trained models trained on large-scale data have shown unprecedented potential, and their release has had a significant impact. However, most of the released models specialize in the English language, and thus, AI democratization in non-English-speaking communities is lagging significantly. To reduce this gap in AI access, we released Generative Pre-trained Transformer (GPT), Contrastive Language and Image Pre-training (CLIP), Stable Diffusion, and Hidden-unit Bidirectional Encoder Representations from Transformers (HuBERT) pre-trained in Japanese. By providing these models, users can freely interface with AI that aligns with Japanese cultural values and ensures the identity of Japanese culture, thus enhancing the democratization of AI. Additionally, experiments showed that pre-trained models specialized for Japanese can efficiently achieve high performance in Japanese tasks.

Ni Wayan Meidariani, Ni Luh Gede Meilantari, Made Henra Dwikarmawan Sudipa

Ontological metaphor is used to conceptualize something abstract into something real. Ontological metaphors are found in sentences on hotel websites used as a form of promotion. This study has two objectives: 1) to find out the types of ontological Japanese metaphors on Japanese-language hotel websites in Bali, and 2) to explain the conceptual meaning of ontological metaphors on Japanese-language hotel websites in Bali. This study is qualitative research and takes a phenomenological approach. The research phase begins by observing the sentences on four hotel websites in South Bali. Furthermore, the data was collected using the observation method in conjunction with reading and note-taking techniques. The theory of conceptual metaphor developed by Lakoff and Johnson is used to analyze ontological metaphors. The data were analyzed using the identity method, namely explaining the conceptual meaning contained in the ontological metaphor. Ontological metaphors on hotel websites emphasize service and luxury. Services and luxuries as something abstract are visualized as things that can be felt and enjoyed by humans, therefore creating a metaphorical expression in the form of "enjoy the luxury" (zeitaku o sashimi kudasai). The results of the study show that there are four conceptualizations of ontological metaphors on Japanese-language hotel websites in Bali, namely: 1) stress or fatigue is something that can be eliminated; 2) service is something that can be felt; 3) luxury is something that can be enjoyed; and 4) memories are something luxurious. Children's language politeness and the role of parents in supervising and educating children on this platform are very important.