Accurate Translation Research Articles

A Comparative Analysis of Japanese Learners’ Translation Bias Using Neurosemantic Analysis

Abstract In today’s increasingly frequent cultural exchanges between China and Japan, accurate and error-free Japanese translation has become an inevitable choice for cross-cultural communication. In this paper, based on twin neural network and attention mechanism, BiLSTM model is combined with sentence semantic similarity matching algorithm to construct a Japanese translation bias sentence semantic similarity model. The Japanese corpus data were collected and preprocessed by Python technology, and the Japanese translation corpus database was searched and counted using Wordsmith and AntConc tools. For the Japanese learners’ translation bias in the Japanese translation process, a comparative analysis was carried out in several aspects, such as end-of-sentence modal expressions, consecutive translations, and word frequency effects. The study results show that the difference in the frequency distribution of Japanese learners’ modal expressions is only 4.66% compared with that of native speakers of Japanese. Still, the difference between the two is significant at the 1% level, and the difference in the frequency of Japanese learners’ use of the modal expression “yes” is 56 sentences per 10,000 sentences. The frequency of Japanese learners’ use of successive expressions was 30.1 percentage points higher than that of native speakers. The neural semantic analysis method combined with the Japanese translation corpus can clarify the translation bias of Japanese learners in the process of Japanese translation, which can provide a reference for enhancing the translation quality of Japanese learning.

Design and Implementation of Foreign Language Recognition and Translation APP Based on Artificial Intelligence

Globalization has created the demand for cross-language communication, which has promoted the development of machine translation applications (APPs) based on artificial intelligence (AI) for foreign language recognition and translation. The purpose of this study is to develop and implement a mobile application program that can accurately identify and translate foreign languages. APP adopts advanced artificial intelligence technology, uses optical character recognition (OCR) technology to identify the text in images, and uses neural network architecture based on transformer for machine translation. In the data preprocessing stage, text cleaning, word segmentation and other preprocessing steps are performed to create accurate translation input. A translation model is trained on a large bilingual mapping data set to learn the mapping knowledge relationship between the source language and the target language. After a series of tests and experiments, the application of foreign language identification and translation shows the high accuracy and speed of multilingual input and output. The accuracy of this application is 0.9, and the maximum delay is only 180 milliseconds. Although there is still room for improvement in the background of professional fields or complex scenes, this application is an effective tool for cross-language communication. Future work should focus on further optimizing translation models, improving the accuracy of translation for specific domain terms, and enhancing the personalized service capabilities of the APP.

Validation of a Finite Element Simulation for Predicting Individual Knee Joint Kinematics.

Goal: We introduce an in-vivo validated finite element (FE) simulation approach for predicting individual knee joint kinematics. Our vision is to improve clinicians' understanding of the complex individual anatomy and potential pathologies to improve treatment and restore physiological joint kinematics. Methods: Our 3D FE modeling approach for individual human knee joints is based on segmentation of anatomical structures extracted from routine static magnetic resonance (MR) images. We validate the predictive abilities of our model using static MR images of the knees of eleven healthy volunteers in dedicated knee poses, which are achieved using a customized MR-compatible pneumatic loading device. Results: Our FE simulations reach an average translational accuracy of 2 mm and an average angular accuracy of 1[Formula: see text] compared to the reference knee pose. Conclusions: Reaching high accuracy, our individual FE model can be used in the decision-making process to restore knee joint stability and functionality after various knee injuries.

Language System Path of Intelligent Machine Translation

Machine translation is an important means of language services. This article proposes a theoretical framework for language systems, and uses deep learning to study and discuss the intelligentization of machine translation from the three dimensions of language system levels, structures, and functions. At the language system level, machine translation needs to follow basic rules to realize automatic identification and processing of language information; at the structural level, machine translation needs to use contextual knowledge and domain knowledge for information matching while maintaining the semantic integrity of the translation; at the functional level, machine translation requires semantic analysis and semantic reasoning based on language context. In the end, the translation accuracy rate increased from an average of 83.18% to 94.42%.

Applying Knowledge Mapping Techniques to Enhance Contextual Understanding and Accurate Correspondence in Translating Metaphorical Information in Japanese Literature

Abstract Metaphorical information is prevalent in literary texts, and understanding the cultural and historical contexts of Japanese literature can significantly enhance the translation of its metaphors. This paper introduces a knowledge graph specifically designed for translating metaphorical content in Japanese literary works. This graph facilitates the categorization, extraction, and storage of symbolic information. To refine the knowledge graph further, the RAEA model is employed, coupled with a distinct attention mechanism assigned to each node of symbolic information. This approach significantly improves the entity alignment in translations, thereby enhancing translational accuracy. In constructing a dataset that includes background symbolic information, the knowledge graph demonstrated a precision of 0.9256 and a recall of 0.9136. Additionally, the graph achieved an average Mean Reciprocal Rank (MRR) index of 0.810, markedly surpassing traditional translation models. This paper’s knowledge graph thus offers an effective methodology for the precise translation and interpretation of symbolic information in Japanese literature, aiding in the deeper comprehension and accurate representation of such content.

Integration and Innovation of Artificial Intelligence and Traditional English Translation Methods

Abstract In this study, we employ autoregressive and neural machine translation models to process natural language. Our exploration of AI translation workflows encompasses three key aspects: the encoder-decoder framework, text feature representation, and translation derivation methodologies. Subsequently, we identify the core evaluation indices essential for assessing intelligent translation systems. An innovative translation model is constructed by amalgamating AI-driven and traditional English translation techniques. This model is scrutinized for its effectiveness through various lenses, including the quality of English-to-Chinese poetry translations and manual evaluations. Comparative analysis of the proposed translation method with other extant methods across diverse datasets reveals superior performance metrics: the BLEU score consistently exceeds 4.5 across all three test sets, and the METEOR score ranges between 4.3 and 4.6, surpassing competing methods. Additionally, translation accuracy for sentences of varying lengths in the source language is maintained between 85% and 96%. The objective of this research is to conduct a comprehensive examination of the integration of AI English translation with conventional methodologies, aiming to foster innovative theoretical contributions and practical advancements in the field.

The Intersection of Linguistics and Information Technology in the Global Communication of Martial Arts Culture

Abstract In the course of global dissemination, Wushu culture encounters numerous linguistic challenges that significantly impede the translation quality and dissemination efficacy of its content. These challenges include terminology barriers, cultural heterogeneity, linguistic style conventions, and audience applicability. This paper initially explores the representation of natural language within computational systems and examines the foundational frameworks of language models. Subsequently, we algorithmically model the basic architecture of neural machine translation and text feature extraction. To address the gradient error issue in backpropagation, we employ the Long Short-Term Memory (LSTM) algorithm. Furthermore, we construct a neural machine translation model that incorporates an enhanced attention mechanism within the LSTM framework. To refine this model, we implement data augmentation techniques, aiming to optimize performance and improve translation accuracy in the context of Wushu's multifaceted linguistic landscape. On this basis, the translation effect of martial arts content is tested and simultaneously used to retranslate 40 pieces of the hottest overseas martial arts culture content. The quality of the translated text before and after retranslation is analyzed to analyze the enhancement effect of the model on the impact of the global dissemination of martial arts culture. It is found that the model in this paper has the best performance in both directions of English-to-Chinese and Chinese-to-English translation, with precision and recall scores of (0.908,0.876) and (0.915,0.922), and F1 values of 0.869 and 0.844, which make the performance stable. In the retranslation and translation quality test of popular martial arts video content, compared with the total penalty score of 1013.7 points before retranslation, the penalty score of the sample after retranslation totaled 246.2 points, a significant drop of 767.5 points, and this paper's model has a substantial effect on the retranslation of martial arts content. This study presents research ideas and practical methods from the perspective of information technology to enhance the global communication capabilities of martial arts culture and establish the international influence of Chinese culture.

Improving Speech Translation Accuracy and Time Efficiency With Fine-Tuned wav2vec 2.0-Based Speech Segmentation

Improving Speech Translation Accuracy and Time Efficiency With Fine-Tuned wav2vec 2.0-Based Speech Segmentation

Identification and Correction of Improved GLR Algorithm in English Translation Teaching

Abstract In this paper, after clarifying the common types of errors in English translation teaching, in order to achieve the improvement of English translation teaching, combined with the GLR algorithm for English phrase recognition and analysis, PCFG English syntactic analysis model and HDSM lexicalization model are introduced for the optimization of GLR algorithm, which constitutes the PCFG-HDSM model. Analyze the process of English translation error recognition and correction with an improved GLR algorithm and realize the improvement of the GLR algorithm. Compare the performance of the English translation grammar analysis generator and determine the ratio of pure grammar analysis time to total analysis time. Examine the English translation accuracy of the improved GLR algorithm by combining the training corpus and evaluating it using LP and LR metrics. Analyze practical teaching applications by classifying the structure of English translation topics and using the improved GLR algorithm. The improved GLR algorithm is able to achieve more than 80% of English translation recognition and correction rates, which enhances students’ scores on English translation topics and promotes the development of English translation teaching.

Research on the Application of Natural Language Processing Technology in English Translation Quality Control

Abstract Machine translation is an important research area in natural language processing. In this paper, we propose an innovative fusion translation model that combines the slicing method and the alignment method and select articles from different domains for experiments to explore the translation effects of the proposed method. The experiments show that the proposed CRF sequence annotation cut-scoring method performs excellently, with F-values of 86.7%, 89.0%, and 87.4% for the three domains of computer science, civil engineering, and medicine, respectively. The hybrid alignment method based on the length and lexical information also performs well, both in terms of correctness and recall and the hybrid alignment method is able to obtain better results than the length or lexical information methods alone. Putting the proposed method into the translation accuracy test, the BLEU score of the cut-and-align fusion translation model is improved to 11.08, while the NIST score is improved to 3.6468, which is a significant improvement in the translation quality of English.

A Quantitative Impact Assessment of English Translation Errors on the Authenticity of News Dissemination

Abstract To improve the accuracy of news communication between readers and audiences, it is necessary to avoid the errors generated in the process of news translation so as to make the English translation of news content expression more in line with the actual situation, thus ensuring the authenticity of news dissemination. In this paper, the MapReduce multiple regression model is constructed by optimizing the classical multiple linear regression model in terms of maximum likelihood estimation and gradient descent algorithm with the aim of reducing the errors in the process of English translation of news. This model is used to analyze the errors generated by the English translation process and finally proposes a method for improving translation accuracy based on the factors causing the errors. After testing, the F-value, P-value, and R² of the degree of fit of the MapReduce model are 54.39, 0.005, and 0.893, respectively. Furthermore, the model passed the significance test. The Pearson coefficients of the 4 types of translation errors in the MapReduce multiple linear regression model were −0.673, −0.622, −0.584, and −0.736, respectively, all of which were significantly negatively correlated with the truthfulness of news dissemination at the 1% level. The model analyzes that the three kinds of translation errors are basically between 2%-4%, 7%-20%, and 2%-4%, and puts forward reasonable opinions on the avoidance of the four kinds of errors, namely, “pragmatic translation, cultural translation, linguistic translation and text-specific translation”, which generate errors in the process of the English translation of news.

«Смерть Лопатинского» Ф. Булгарина в переложениях финских авторов XIX в.

The article explores the Swedish translation and poetic adaptations of F. Bulgarin’s “war story” “The Death of Lopatinsky,” published in Finland at the turn of the 1830s and 1840s. The article documents and explains the differences between the Swedish translations and the original Russian work. It also notes the reaction of the Finnish readership to the Swedish texts. The response to the relatively accurate translation of Bulgarin’s story published in the newspaper “Wasa tidning” (January 1839) was an article in “Borgå tidning” (May 1839), containing a truthful, in contrast to the Russian version, description of the death of Lieutenant Lopatinsky in September 1808. The article discusses Janne Lundmark’s poem “The Death of Lopatinsky, and the Voices at the Tomb,” which was published in Helsingborg in 1843. This poem is a poetic reworking of Bulgarin’s text and includes references to several characters from Scandinavian mythology, with the Houris being the most prominent. The article suggests that Lundmark indicates the eastern origin of the hero of the poem in this way. The article also notes that Valkyries and Houris often form a pair of “maidens of Paradise” in Swedish literature from the first half of the 19th century. Lundmark probably takes this into account. Finally, the article mentions that Lundmark’s poem is one of several works by Swedish-speaking authors from the 17th–18th centuries that are dedicated to the death of a hero.

Enhancing Translation Research on Chinese Silk Terminology: A Critical Review from the Perspective of Skopos Theory

As China’s international status continues to improve and its foreign trade and exchanges become more and more frequent, the development of China’s silk industry has received more and more attention. As a bridge for China’s foreign trade in silk industry, its translation will take on important responsibilities in the future. The accurate translation of Chinese silk terminology is the most direct, authoritative and comprehensive source of information about Chinese silk culture for people around the world. In the new era, a better standardization of Chinese silk terminology translation is a new requirement for the international community to have a more comprehensive understanding of Chinese silk and culture in the future. Therefore, it is crucial to explore and study translation theories in translation practice in the context of Chinese silk terminology.

Unexpected discoveries in comparative legal studies of criminal proceedings

Comparative legal studies have always been a significant part of scientific research of the problems of criminal procedure.At present, comparative studiesof criminal procedure have become more demanded because of the need of constant international exchange of legislative and law enforcement experience. In this regard, the requirements for the quality of these studies are becoming higher.Currently, in scientific researches are usually used legislative sources only in the original language.During the comparative analysis not only the provisions of normative legal acts in their general legal meaning are compared, but also specific original terms in accordance with the context.A comprehensive legal and linguistic analysis of legislative provisions used in different national legal systems allows us to identify new meanings in the compared laws, assess the effectiveness of legal regulation of similar public relations in different states, consciously adopt or refuse foreign legislative experience.The author analyzes the published comparative studieson the problems of choosing preventive measures in the criminal process of the Swiss Confederation, the witness immunity ofprofessional secrecy keeper and the reform of theadvocacy in the Federal Republic of Germany. Based on the results of the analysis, the author claims that an accurate translation of specific legislative terms used in these states allows us to more fully reveal the meaning of regulatory legal prescriptions and to avoid attempts to fit the legal concepts familiar to Russian and Russian-speaking lawyers into a foreign regulatory scope.In this context, the problems of the theory and practice of the Russian criminal process concerning detention in pre-trial and judicialcriminal proceedings, witness immunity of alawyer, the role of a lawyer in the administration of justice are considered.

THE ARTISTIC FEATURES AND STYLISTIC EFFECTS OF TRANSLATION OF CHINESE AND KAZAKH PROVERBS

This study delves into the extensive body of research on proverbs in both Chinese and Kazakh languages. Scholars examining Chinese proverbs often approach the categorization and conceptual distinctions from three primary perspectives: 1) proverbs and sayings are grouped under the broader concept of "common sayings"; 2) within the concept of "proverbs," both terms are encompassed under "folk speech"; and 3) in translation, "proverbs" correspond to the Chinese term for proverbs, while "common sayings" align with the concept of proverbs as understood in Kazakh. Our research adopts the third perspective. Additionally, we explore the classification of Chinese expressions known as "歇后语" (Afterwords), which translates into Kazakh as "аллегориялық астарлы сөз" (metaphorical word). Unlike Chinese, where proverbs and proverbs are distinct, Kazakh language sources such as books, collections, and dictionaries often conflate the two, distinguishing proverbs with dashes and writing proverbs as a single unit without commas. Therefore, distinguishing between proverbs, sayings, and metaphors is crucial for accurate translation and understanding in both languages.

ОТ «ЗАМКА СТРАХА» К «ТРЕМ ТОЛСТЯКАМ»: СКАЗКА ЮРИЯ ОЛЕШИ НА ИТАЛЬЯНСКОМ ЯЗЫКЕ

In the 20th century, Russia played an important role in the field of translated children’s literature, although, compared to other foreign children’s literature, the popularity it enjoyed — particularly in the second half of the 20th century — was always less significant. Nevertheless, some works of fiction have managed to find their place on the book market and have been translated into Italian several times. This article takes into account the success of the book The Three Fat Men by Yuri Olesha in Italy, which was published and adapted several times during the second half of the 20th century. The analysis highlights the strategies and approach of each translator (Carullo, Leone, Coïsson) within the framework of the methodology of analysis adopted in the field of translation studies: Carullo offers a more free translation, which corresponds to the translation tradition of that period, when the search for an accurate translation was not a priority of the publishing market. Leone’s translation sets out to find a compromise for the dual addressee (child and adult), in contrast to Coïsson, who turns exclusively to the adult reader. Much attention is paid to text and paratext, the role of illustrations and other constituents of the book as a cultural product. The linguistic and textual analyses allow us to draw some conclusions about the dominants in the translation strategy of a particular translator.

The impact of technology on Translation

Technology development has had a significant impact on translation. This research paper attempts to uncover the impact of technology on translation from translators and translation experts’ perspectives. It explores how translators view the effects of technology on their profession as well as the difficulties they encounter when dealing with such machine tools. An eclectic method is followed in the study, viz., expert interviews and a survey of professional translators, to grasp the attitudes towards technology in the translation industry. The findings show that people in the field of translation inconsistently opine about the current situation and varyingly speculate about the future of the relation between translation and technology. The study reveals that the accuracy of machine translation, the requirement for ongoing learning and training, and some moral issues with the application of translation technologies are the major concerns among human translators.

Feasibility of using corpora as a tool in translation practice

Professional translators commonly employ various tools to streamline and ensure the accuracy and consistency of their work. One such tool is corpora, which becomes particularly crucial when dealing with authentic texts like those from the United Nations (UN). This study focuses on qualitatively and quantitatively investigating the impact of using UN parallel corpora on novice translators. The research aims to address two main questions: Does the use of parallel corpora significantly improve translation performance, and in what specific areas does it contribute to improvement? To examine this, 30 students were given two translation tasks of equal difficulty level. The first task was completed without utilizing the UN corpora, while the second task involved their incorporation. A t-test was conducted to determine the significance of any differences observed among the participants. Findings highlight the vital role of corpora in translation classes that focus on United Nations texts. Through exposure to authentic source material, students gain a deeper understanding of the complex terminology used in these documents. Additionally, corpora enable students to identify language usage patterns, including syntax, collocations, and discourse structures. Equipped with this knowledge, translators are better able to produce translations that accurately convey intended meaning and register. Notably, the results of the t-test indicate a significant positive impact of corpora on student achievement.

Translation of English Modals in the Novel Entitled Deck The Halls

This study analyzes the translation of English modals into Indonesian within the context of the novel "Deck the Halls" by Mary Higgins Clark and Carol Higgins Clark. Modals, such as "can," "could," "may," "might," "should," "would," and "must," are crucial in expressing nuances of possibility, necessity, permission, and ability. Their accurate translation is vital for preserving the narrative's tone, intent, and subtlety. This study examines how these English modals are rendered in Indonesian, highlighting translation strategies employed to convey the original meaning effectively. The analysis reveals that modals are often translated through literal and contextual approaches. For instance, "must" is translated as "harus" to convey strong necessity, while "might" is rendered as "mungkin" to express uncertainty. The study also explores challenges such as nuance loss and context sensitivity, which arise due to structural and cultural differences between English and Indonesian. The effectiveness of the translation is evaluated based on how well it retains the original modals' meanings and narrative functions. Overall, this analysis demonstrates that while translating English modals involves navigating complex linguistic and cultural factors, the strategies employed in "Deck the Halls" generally succeed in preserving the narrative's intended tone and meaning.

Çeviribiliminin Yapay Zeka (YZ) ile Geliştirilmesi: Zorluklar, İmkânlar ve Öneriler

This theoretical study delves into the symbiotic relationship between Translation Studies and Artificial Intelligence (AI), emphasizing the need for collaboration between these two fields. The study explores the challenges and opportunities for developing Translation Studies with AI and presents proposals for advancing the integration of AI in the field. The integration of AI in translation practices has the potential to enhance translation efficiency, overcome language barriers, and expand access to the information. However, this integration also raises the important ethical considerations, such as the role of human expertise in translation, the accuracy and cultural appropriateness of translations, and the impact of AI on the workforce. The study highlights the importance of integrating AI-related topics into the curriculum of Translation Studies programs, fostering collaborative research projects between scholars and AI developers, and addressing the need to bridge the gap between AI's IQ and EQ capabilities. Translation Studies can play a crucial role in improving AI systems' accuracy and cultural sensitivity in translation by providing valuable insights into the cultural nuances, context, and ethical considerations. By leveraging the expertise of Translation Studies, AI developers and researchers can enhance the performance of AI-based translation systems, ultimately improving the quality and impact of AI in translation. Therefore, this study supports the collaboration between Translation Studies and AI to improve the quality of translation services and promote the widespread use of culturally sensitive translations.