Analyzing the impact of deep learning algorithms and fuzzy logic approach for remote English translation.

A remote English translation is used for assisting with on-demand support for adaptable sentence conversion and language understanding. The problem with on-demand translations is the precision verification of the words used. This article addresses the precision problem by assimilating deep learning and fuzzy decision algorithm for remote translation support. The method named Fusion-dependent Precision Translation Approach (FPTA) conducts a series of recurrent validations on word usage and sentence completion for the given inputs. First, the completed sentences are verified using the understandability and meaning intended using deep learning in two recurrent layers. The first layer is responsible for identifying word placement and understandability and the second is responsible for meaning verification. The recurrent training is tuned using a fuzzy decision algorithm by selecting the maximum best-afford solution. The constraint's understandability and meaning are augmented for tuning the outputs by preventing errors consequently. In precise, the error sequences are identified from the first layer for fuzzification across various inputs. This process improves the word adaptability from different languages reducing errors (12.49%) and improves the understandability (11.57%) for various translated sentences.

Applying augmented reality multimedia technology to construct a platform for translation and teaching system.

This paper investigates the integration of augmented reality (AR) technology into English translation teaching for college students, emphasizing the pivotal role of innovative teaching methods in enhancing students' translation skills and learning experiences. To address the issue of insufficient interest in English translation teaching, the paper initially assesses the purpose and significance of learning English translation through a questionnaire survey, elucidating challenges encountered in English language acquisition. Subsequently, adhering to AR principles, a teaching demonstration platform rooted in AR technology is conceived and developed, intricately aligned with English translation instruction. The platform serves as a solution to issues in English learning, such as inadequate course comprehension, low utilization of teaching resources, and instructors' lack of experience. The research culminates in the analysis of survey results, wherein the quantitative disparities in translation ability between students utilizing the research platform and those subjected to traditional teaching methods are examined. The findings underscore the positive impact of the AR-based research platform on improving students' translation proficiency. The AR platform heightens learners' engagement in the learning process, contributes to constructing a robust knowledge framework, and enhances overall learning outcomes. The platform offers educators opportunities to optimize experimental courses and elevate teaching standards. The paper's outcomes present novel pedagogical scenarios for learners, propose technical solutions for other technical disciplines and furnish a theoretical foundation and application model for a new generation of experimental demonstration platforms.

Transfer learning-based English translation text classification in a multimedia network environment.

In recent years, with the rapid development of the Internet and multimedia technology, English translation text classification has played an important role in various industries. However, English translation remains a complex and difficult problem. Seeking an efficient and accurate English translation method has become an urgent problem to be solved. The study first elucidated the possibility of the development of transfer learning technology in multimedia environments, which was recognized. Then, previous research on this issue, as well as the Bidirectional Encoder Representations from Transformers (BERT) model, the attention mechanism and bidirectional long short-term memory (Att-BILSTM) model, and the transfer learning based cross domain model (TLCM) and their theoretical foundations, were comprehensively explained. Through the application of transfer learning in multimedia network technology, we deconstructed and integrated these methods. A new text classification technology fusion model, the BATCL transfer learning model, has been established. We analyzed its requirements and label classification methods, proposed a data preprocessing method, and completed experiments to analyze different influencing factors. The research results indicate that the classification system obtained from the study has a similar trend to the BERT model at the macro level, and the classification method proposed in this study can surpass the BERT model by up to 28%. The classification accuracy of the Att-BILSTM model improves over time, but it does not exceed the classification accuracy of the method proposed in this study. This study not only helps to improve the accuracy of English translation, but also enhances the efficiency of machine learning algorithms, providing a new approach for solving English translation problems.

Neural machine translation of clinical text: an empirical investigation into multilingual pre-trained language models and transfer-learning.

Clinical text and documents contain very rich information and knowledge in healthcare, and their processing using state-of-the-art language technology becomes very important for building intelligent systems for supporting healthcare and social good. This processing includes creating language understanding models and translating resources into other natural languages to share domain-specific cross-lingual knowledge. In this work, we conduct investigations on clinical text machine translation by examining multilingual neural network models using deep learning such as Transformer based structures. Furthermore, to address the language resource imbalance issue, we also carry out experiments using a transfer learning methodology based on massive multilingual pre-trained language models (MMPLMs). The experimental results on three sub-tasks including (1) clinical case (CC), (2) clinical terminology (CT), and (3) ontological concept (OC) show that our models achieved top-level performances in the ClinSpEn-2022 shared task on English-Spanish clinical domain data. Furthermore, our expert-based human evaluations demonstrate that the small-sized pre-trained language model (PLM) outperformed the other two extra-large language models by a large margin in the clinical domain fine-tuning, which finding was never reported in the field. Finally, the transfer learning method works well in our experimental setting using the WMT21fb model to accommodate a new language space Spanish that was not seen at the pre-training stage within WMT21fb itself, which deserves more exploitation for clinical knowledge transformation, e.g. to investigate into more languages. These research findings can shed some light on domain-specific machine translation development, especially in clinical and healthcare fields. Further research projects can be carried out based on our work to improve healthcare text analytics and knowledge transformation. Our data is openly available for research purposes at: https://github.com/HECTA-UoM/ClinicalNMT.

A high performance computing technology powered multimedia fusion model in university English translation.

Various forms of materials, such as pictures, videos and texts, have rapidly brought the college English translation teaching model into the era of multimedia integration. This makes it difficult for English teachers to improve college English translation by using unique materials, so as to form their own unique teaching style. In view of this, a multimedia comprehensive English translation framework based on the combination of big data technology and multimedia teaching mode is proposed. At the same time, the idea of building the framework is introduced from two perspectives: the integration of big data technology and multimedia, and the integration of multimedia and English teaching process. Then, a recursive neural network algorithm based on ant colony optimization algorithm is proposed and tested. Finally, the simulation results show that the proposed method has significantly improved the accuracy and retention rate, indicating the effectiveness of the framework.

Bilingual Conversion in the Translation of ICH Terms: A Study on the Psychological Processes of Translators.

Intangible cultural heritage (ICH) terms are unique expressions of cultural knowledge and practices that are deeply rooted in a particular region or community. Accurately translating ICH terms is crucial for sharing this knowledge and promoting cross-cultural understanding. However, the complex nature of ICH terms, including their regional and cultural specificity, means that mistranslations can easily occur during the translation process. In addition to linguistic and cultural barriers, psychological factors can also impact the accuracy of translations. Translation psychology, a new discipline that examines the psychological process of bilingual conversion and its cognitive mechanisms, can provide insights into the translation of ICH terms. This paper proposes an information processing model of translating ICH terms based on translation psychology, which examines the psychological processes of translators during the translation of Chinese ICH terms into English. Through questionnaires and translation exercises, the study compares and analyzes the psychological activity process of the translators, verifies the expression of translation psychology in the translation of ICH terms, and identifies the characteristics of students' translations. The study's subjects were non-English major sophomores with diverse academic backgrounds, randomly sampled from a representative polytechnic university in Guangdong. The findings of this study are significant for improving the quality of translations and promoting cross-cultural understanding of ICH terms. By understanding the psychological factors involved in the translation of ICH terms, we can overcome language and cultural barriers and accurately convey the rich cultural heritage embodied in these terms.

Translating Akkadian to English with neural machine translation.

Cuneiform is one of the earliest writing systems in recorded human history (ca. 3,400 BCE-75 CE). Hundreds of thousands of such texts were found over the last two centuries, most of which are written in Sumerian and Akkadian. We show the high potential in assisting scholars and interested laypeople alike, by using natural language processing (NLP) methods such as convolutional neural networks (CNN), to automatically translate Akkadian from cuneiform Unicode glyphs directly to English (C2E) and from transliteration to English (T2E). We show that high-quality translations can be obtained when translating directly from cuneiform to English, as we get 36.52 and 37.47 Best Bilingual Evaluation Understudy 4 (BLEU4) scores for C2E and T2E, respectively. For C2E, our model is better than the translation memory baseline in 9.43, and for T2E, the difference is even higher and stands at 13.96. The model achieves best results in short- and medium-length sentences (c. 118 or less characters). As the number of digitized texts grows, the model can be improved by further training as part of a human-in-the-loop system which corrects the results.

Reproducing experiential meaning in translation: A systemic functional linguistics analysis on translating ancient Chinese poetry and prose in political texts.

Ancient Chinese poetry and prose (ACPP) are the essence of traditional Chinese culture and also literary gems of the world. Despite the long tradition of previous Chinese Presidents using ACPP in their political addresses, the translation work on the three volumes of Xi Jinping: The Governance of China with much ACPP still poses a daunting challenge to the translation of literary texts in non-literary texts. As experiential meaning is inherent in all kinds of texts, literature, and non-literature, this study, drawing on the sights of Halliday's experiential mode of meaning and register theory in Systemic Functional Linguistics (SFL), explored how the ACPP's experiential meaning was rendered in the political texts, and factors motivating transitivity patterns and shift tendencies. Statistics showed that the translations tend to reproduce the experiential meaning such that it involves more representations of the flow of events and the creation of relationships among entities, focusing more on construing the experience of the physical world rather than personal emotions, feelings, or cognition. Besides, the target text is also inclined to simplify the experiential meaning by compressing and omitting unnecessary transitivity processes and the participant and circumstance nominalization. This research found that the factors responsible for such tendencies include the features of political texts, language differences, the distribution of process types, the delicacy of the transitivity system, and register variations of fields of activity. With these findings, the study is expected to contribute to the SFL approach of studying literary translation in non-literary texts through the prism of experiential meaning and offer guidance in the translation of political literature with ACPP.

Emotional analysis of evaluation discourse in business English translation based on language big data mining of public health environment.

Purpose: This paper conducts sentiment analysis on the evaluation discourse of business English translation based on language big data mining of public health environment, and aims to find a reasonable algorithm to conduct detailed research on all aspects of sentiment analysis. Methodology: This paper focuses on three areas of sentiment information, extraction, sentiment information retrieval, and sentiment information submission, using scale analysis and feedback analysis, combined with related algorithms of big data mining technology, such as decision trees and clustering algorithms, through the level of emotional words appearing in the corpus, phrase-level, text-level, etc., and combine the text model with the combined reliability to output the evaluation object and evaluation feature separately, and propose an evaluation method to calculate the sensitivity of the evaluation feature, so as to accurately improve the sensitivity of the evaluation feature. It is mainly divided into two categories for data analysis. One is to focus on the public health environment of the characteristics of business English translation itself, and the other is to conduct research on the application of big data mining in the evaluation of translation discourse. Research findings: The research data show that the smallest gap between the sentiment orientation of the discourse evaluation perspective is the output of the language discourse, and the smallest gap in the attributes of the evaluation object is at the phrase level, and the gap value is 3.5; for the evaluation object, the maximum difference is 3.4. Research implications: With the development of science and technology and the economy, the public health environment has become more and more complex, and business English translation has received more and more attention. The sentiment analysis of evaluation discourse in this field is a means of expressing language characteristics. In order to enrich research in this field, the study of this article is necessary. Practical implications: This study has a deeper understanding of the affective analysis of evaluation discourse in public health environment business English translation. The clustering algorithm of big data mining technology applied can provide an important guarantee for the actual conclusion of this research and quantitative analysis of the positive evaluation and criticism of evaluation. To solve the various problems encountered in translation, so as to improve the translator's own translation level, and promote the research of translation methods in Chinese translation.

COVID-19-Combating English with Chinese Characteristics in the CAT's Translations.

During the COVID-19 outbreak, the China Academy of Translation translated and officially released five groups of Key Words to Understand China: The Fight Against COVID-19 for daily precautions, policy publicity, and information dissemination. Based on the translations and relevant data from Chinese and English media, this study makes a tentative analysis of the linguistic, ideological, and cultural features of English used in the translations. The findings are that China English is outstanding with respect to translating some Chinese-specific words and expressions in the translations, which generally results from the method of literal rendering. It is suggested that literal translation and transliteration can be used more frequently in English texts related to big events in order to strengthen the Chinese characteristics of China English as a major variety of world Englishes.

The metonymic mechanism of English translation of Chinese intangible cultural heritage terms from the perspective of cognitive psychology.

The translation of Intangible Cultural Heritage (ICH) terms is an important practical aspect of cross-lingual expressions related to ICH knowledge. Chinese ICH terms are heavily loaded with specific historical and cultural knowledge and regional characteristics. Based on cognitive psychology, this paper analyzes the metonymic mechanism of traditional translation techniques such as substitution in the English translation of Chinese ICH terms. The English translation of Chinese ICH nominal terms can be realized based on the metonymic mechanism of replacing either a superordinate with a subordinate of the linguistic structure or a subordinate of the linguistic structure with a subordinate of the linguistic structure in the pair language, English-Chinese. The English translation of Chinese ICH verbal terms can regard the whole verbal action as an event process and can highlight one aspect of the process through a metonymic mechanism as well. This paper holds that metonymy is an important psychological motivation and cognitive mechanism for translation skills such as substitution as it brings the relationship between the corresponding items of the target language and the source language into a unified interpretation framework. Hence, this may add some significance to the research of translation theory and translation practice. This also contributes to the UN Sustainable Development Goal number 17 which seeks global parternship for sustainable development.

Tracing the translator's voice: A corpus-based study of six English translations of Daxue.

The Translator's voice is the "second" voice in a translated narrative. By tracing a set of textual cues, the translator's voice embedded in the discourse may come to light. This study is based on a self-constructed bilingual parallel corpus which adopts both quantitative and qualitative methods to reveal the translator's voice in six English versions of the Chinese classic Daxue. WordSmith 8.0, CLAWS POS Tagger, and Readability Analyzer were used to analyze the data and investigate the lexical, syntactic, and textual features of the translations of Daxue by David Collie, James Legge, Ku Hungming, Ezra Pound, Chan Wing-Tsit, and Andrew Plaks, respectively. Paratexts of translation-prefaces, introductions, translator's notes, footnotes, and so on, as well as representative examples, were also analyzed by close reading. The findings suggest that each translator's cultural identity, historical background, and motives for producing the translation are made manifest through various linguistic and non-linguistic choices. This study demonstrates that the translator's voice, which is always present along with the author's voice and may take various forms, is deeply associated with the cultural and ideological constructs in which the act of translation is embedded. It is hoped that the results of this research will contribute to an enhanced understanding of the translation and overseas dissemination of the Chinese classic Daxue, and further the study of the translator's voice with the aid of corpus technology.

Peer Feedback in Translation Training: A Quasi-Experiment in an Advanced Chinese-English Translation Course.

Although research on peer feedback in second language teaching and learning has been developed from various perspectives over the past three decades, less is known about feedback in translation settings. This study reports the results of a quasi-experiment with advanced second language learners in a Chinese-English translation course. It examines how effective peer feedback is in improving the quality of translations. The following data were collected from 30 students: their initial translation drafts, the drafts with the feedback of their peers, and the final corrected translations. The whole process was facilitated by computer assistance and under anonymity. It was found that most students drew on direct or indirect corrective feedback while few students drew on metalinguistic corrective feedback. Text genres were also proved to impact the types and counts of peer feedback. An analysis of the accuracy rate of corrections after peer feedback showed that it had a positive impact on translation quality. The findings shed light on the applicability of peer feedback in other pedagogical activities.

Translation, Cross-Cultural Adaptation, and Psychometric Validation of the English Version of the Postural Awareness Scale.

PURPOSE: The Postural Awareness Scale (PAS) was developed among a sample of German speakers to measure self-reported awareness of body posture. The first aim of this study was to conduct an English translation and cross-cultural adaptation of the PAS. The second aim was to assess psychometric properties of the English version of the PAS. METHODS: Forward and backward translations were conducted. The translated scale was then pretested in a small sample of English-speaking adults (n = 30), followed by cognitive interviews. Finally, consensus of the translated scale was achieved among an expert committee (n = 5), resulting in the Postural Awareness Scale-English Version (PAS-E). Psychometric properties of the PAS-E were investigated among a sample of individuals with chronic pain (n = 301) by evaluating factor structure, reliability, and construct validity. Analyses of variance were conducted to calculate differences in PAS-E scores between specific subgroups (pain conditions, sex, and history of mindfulness practice). Linear regression analyses investigated whether the scores on the PAS-E predicted levels of pain, stress, and mood. RESULTS: The results obtained from an exploratory factor analysis showed a two-factor solution and were supported by a confirmatory factor analysis. The scale demonstrated good internal consistency and satisfactory construct validity. No significant differences related to sex at birth or pain duration were found. CONCLUSION: PAS-E demonstrated good psychometric properties, and therefore, can and should be used both for research and clinical practice.

Key factors influencing the TCM nomenclature in international standards.

Amid the globalization of traditional Chinese medicine (TCM), the English translation of related texts is in full swing. Several representative international organizations in fields regarding standardization and healthcare, one after another, have published a series of international standards for TCM nomenclature. With these efforts, the internationalization of TCM has been dramatically advanced. When selecting parallel texts for reference, translators need to be aware of key factors influencing the English translation of TCM terms in international standards, including the distinctive characteristics of this discipline and relevant influences of international standard makers. In this way, proper standards and reasonable English expression can be chosen for specific terms, thus stimulating the effective use of TCM nomenclature with consensus.

A novel phase analysis method for examining fNIRS neuroimaging data associated with Chinese/English sight translation.

In this study, a phase method for analyzing functional near-infrared spectroscopy (fNIRS) signals was developed, which can extract the phase information of fNIRS data by using Hilbert transform. More importantly, the phase analysis method can be further performed to generate the brain phase activation and to construct the brain networks. Meanwhile, the study of translation between Chinese and English has been exciting and interesting from both the language and neuroscience standpoints due to their drastically different linguistic features. In particular, inspecting the brain phase activation and functional connectivity based on the phase data and phase analysis method will enable us to better understand the neural mechanism associated with Chinese/English translation. Our phase analysis results showed that the left prefrontal cortex, including the dorsolateral prefrontal cortex (DLPFC) and frontopolar area, was involved in the translation process of the language pair. In addition, we also discovered that the most significant brain phase activation difference between translating into non-native (English) vs. native (Chinese) language was identified in the Broca's area. As a result, the proposed phase analysis approach can provide us an additional tool to reveal the complex cognitive mechanism associated with Chinese/English sight translation.

The translation strategies of core terms of traditional Chinese medicine based on the Xiang thoughts and English translation of Wuxing / 国际中医中药杂志

As the basic concept and terminology of the theory system of Traditional Chinese Medicine (TCM), Wuxing has rich philosophical connotations. This research takes the term Wuxing as the object, based on the relevance translation theory to analyze the accuracy of the translation of the three authoritative versions of the dictionary, and finally proposes the reference for English translation of core terms of TCM.

Necessity and Suggestions to Including Infantile Tuina Acupoints in TCM International Standard Terminologies / 中国中医药信息杂志

In recent years, many versions of international standard terminologies on TCM have been established and enacted by different authoritative organizations worldwide. However, infantile tuina acupoints have never been included in them. The article illustrated the necessity of including infantile tuina acupoints in the international standard terminologies on TCM from the aspects of history, present state and specificity of these points. It also pointed out some problems of infantile tuina acupoints, such as different records of acupoints numbers, applications in the clinic and strategies applied in their English translation, and suggestions were provided accordingly, hoping that the infantile tuina acupoints can be included in the further revised versions of international standard terminologies on TCM.

Discussion on International Standard of English Translation for TCM Pulse Condition Name Terms / 中国中医药信息杂志

By comparing WHO International Standard Terminologies on Traditional Medicine in the Western Pacific Region with International Standard Chinese-English Basic Nomenclature of Chinese Medicine from the aspects of word-formation methods, translation methods and specific noun terminology translation methods, this article analyzed the advantages and disadvantages in the translation of pulse condition name terms (floating pulse, deep pulse, rapid pulse, slow pulse, feeble pulse, replete pulse kinds of pluse condition, and intermittent pulse, large pulse, soft pulse) in the two International Standards, with a purpose to provide references for the work of the international standardization of TCM terms.

A comparative study on verb translation of four-character pathogenesis TCM terms of ;spleen and stomach / 国际中医中药杂志

Objectives This paper aimed at exploring the principles and strategies of TCM terminology translation by analyzing the translation of four-character pathogenesis TCM terms of spleen and stomach. Methods Among the verb translation of four-character pathogenesis TCM terms of spleen and stomach from the three prominent national and international dictionaries of TCM terminologies, the researcher chose 12 verbs to conduct a comparative study analyzing the similarities and differences of the English translation under the guidance of accuracy and systematization, two main principles of terminology translation. Results A recommended translation version of these 12 verbs was provided. Conclusion This paper suggested that verb transltion is the key in four-character TCM terminology translation, and verb should be translated in the form of noun and V-ing. TCM terminology translation should employ the principle of accuracy and systematization, together with simplicity, nationality and back-translation.