Translation Of Sentences Research Articles

Review of Research on English Translation of Chinese Running Sentences

Review of Research on English Translation of Chinese Running Sentences

Translation Analysis of Negative Sentences in the Zakat Chapter of the Book Al-Fiqh Al-Muyassar

In fiqh books, the translation of negative sentences into Arabic plays a crucial role in accurately explaining Islamic laws. This phenomenon requires translators to pay attention to correct grammatical structures and the use of appropriate technical terms within the context of Islamic law. For example, negative statements that indicate prohibition or disapproval (makruh) must be translated precisely to prevent misunderstandings or mistaken readings. This study aims to analyzes al-jumlah al-manfiyyah in Arabic, translation techniques, and the quality in al-fiqh al-muyassar. Using a descriptive qualitative approach with Spradley's analysis, 93 instances were identified, employing 12 translation techniques. Of these, 82 were accurately translated with high readability, resulting in a final quality score of 2.83. This suggests that readers can comprehend fiqh worship texts and muamalat effectively. Thus, this research significantly advances scholarship in Arabic language research by setting benchmarks for precision and comprehensibility in translating Islamic legal texts. Future researchers should explore the subtleties of interpreting negative sentences in fiqh texts, consider cultural and contextual influences on Islamic legal texts, and establish standardized guidelines for accurate and accessible translations.

대만인 한국어 학습자의 한중 문장 대역 양상 - 대화문 주어를 중심으로

대만인 한국어 학습자의 한중 문장 대역 양상 - 대화문 주어를 중심으로

A Syntactic Analysis Of The Basic Sentence Patterns In Ile Ape Dialect Of Lamaholot Language

This research examines how many basic sentence patterns there are in Ile Ape Dialect of Lamaholot Language, and what are the basic sentence patterns in Ile Ape Dialect of Lamaholot Language. The writer employed descriptive qualitative method to analyze and describe the data in this research. The data source of this research is the native speakers of Lamaholot Language, especially for Ile Ape Dialect. In this research, the writer used two research instruments to support the process of data collection they are, interview guidelines and recording device (smartphone). The data collection techniques applied in this research consist of three (3) techniques, including audio-recording, written documents collection, and elicitation. In order to analyze the data collected, the writer used technique of transcription, sentence translation, sentence selection, sentence analysis, and data description. The result of this research shows that, there are five (5) basic sentence patterns in Ile Ape Dialect of Lamaholot Language, they are: Pattern I: Subject + Verb (S + V); Pattern II: Subject + Verb + Object (S + V + O); Pattern III: Subject + Verb + Direct Object + Indirect Object (S + V + IO + DO); Pattern IV: Subject + Verb + Object + Object Complement (S + V + O + OC); and Pattern V: Subject + Subject Complement (S + SC).

Penerapan Etika Komunikasi Reception Pada Divisi Kantor Depan Dalam Pelayanan Tamu Check In Di Javana Royal Vila Seminyak Bali

The Increasing competition among accommodation supplies require it to keep optimizing its services in order to give the impression of loyalty to guests to stay. In more specific case, receptionists hold important rules to improve their services, especially in communication ethics. This study is conducted in Javana Royal Villa Seminyak Bali, under the title of Penerapan Etika Komunikasi Reception Pada Front Office Department Dalam Pelayanan Tamu Check in di Javana Royal Villa Seminyak. Bali. This research aims to determine the application of reception communication ethics and the influence of the application of reception communication ethics toward room occupancy rate at Javana Royal Villa Seminyak Bali. This study uses qualitative descriptive in which the translation of words or sentences are explained in the presentation. Moreover, the data collection techniques used are observation, interviews and documentation. The types of data used are primary data and secondary data. The study showed that by not concerning attention to communication ethics, it will greatly impact the comfort of guests in staying which results in bad reviews on the online travel agent so that in this case it certainly has a huge impact on the level of room reservations or on room occupancy in Javana Royal Villa Seminyak Bali.

Research on the Actual Sentence Partition and Translation of Chinese Cultural Landscape Discourses Based on Natural Language Processing Technology

In recent years, ChatGPT has been extensively applied across various fields, with translation being one of them. The objective of this study is to investigate the influence of Natural Language Processing (NLP) technology on the translation process. The research method involved utilizing the concept of Actual Sentence Partition (ASP) within the framework of Function Sentence Perspective (FSP). ASP, introduced by V. Mathesius, the founder of the Prague School, divides sentences into the point of departure and the nucleus of an utterance, providing insights into their communicative and semantic characteristics. Conversely, Formal Sentence Division (FSD) solely focuses on marking grammatical elements without identifying the correct ASP, resulting in ambiguity and inaccuracy. In Chinese discourse, incomplete sentences are commonly observed, including the omission of known information and the use of multiple clauses. Consequently, when translating from Chinese to English, it is crucial to appropriately visualize the hidden information in Chinese and analyze Chinese discourse using ASP to reconstruct its equivalent in English. The findings of this study emphasize the significance of ASP in translation. By understanding the ASP, translators can better comprehend the intention and meaning behind Chinese discourse, ensuring a more accurate and faithful representation in English. Therefore, the application of ASP in translation serves as a valuable tool for bridging the linguistic and cultural gaps between languages. In conclusion, ASP, as a pivotal concept in FSP, offers a comprehensive framework for understanding and translating complex sentence structures in Chinese discourse. By utilizing ASP, translators can capture the communicative and semantic nuances of Chinese sentences, leading to more accurate and effective translation outcomes..

A Report on E-C Translation of This May Hurt a Little

Humorous fiction, as a form of popular literature, focuses on real-life episodes that are laugh-out-loud funny. The protagonists of such novels are often characterized by comical or silly traits, or fools who always meet with misfortune in their acts of kindness and helpfulness. By skillfully depicting the weaknesses and flaws of these characters as well as a series of coincidences and misunderstandings, humor novels successfully reflect the real face of life and the author's creative ideas. This form of literature not only brings readers a relaxing and enjoyable reading experience, but also allows them to appreciate the fun and wisdom of life while reading. The author of the translated material is Eric Nicol, a writer who specializes in writing humorous works and has won numerous awards related to humorous books. The work, entitled This May Hurt a Little, tells a heartbreaking story about the tragic loss of the main character's decaying tooth and the ups and downs of his emotions during a visit to the dentist. The author describes with sardonic wit how he copes with his rotting and bleeding tooth. This paper chooses Eugene Nida's Functional Equivalence to analyze the humorous novel in an attempt to preserve the style and linguistic expressions of the original text, so that the target language readers can get the same feeling as the readers of the original text. The content of this paper includes 5 parts. The first part is an introduction to the work and the author as well as the linguistic feature; the second part is an introduction of the theory of functional equivalence translation; the third part is an introduction of the translation process; the fourth part is a case study under the theory of functional equivalence translation including the translation of words and sentences, and the fifth part is the conclusion, i.e., the enlightenment and the lesson.

The Application of Contextual Integration in English Language Learning

In the process of social development, language plays a crucial role. It serves not only as a carrier of thought and culture but also as a fundamental tool for communication and exchange among individuals. In the journey of learning English, the integration of context can effectively aid students in understanding and mastering the language’s meaning, facilitating accurate translation of relevant sentences. From the perspective of contemporary English language learning, context integration can better elucidate the relationships within language contexts, encompassing factors such as time, space, and objects. Therefore, context integration holds significant practical importance in English language acquisition. It not only enhances learning efficiency but also enables students to accurately comprehend the meaning conveyed in English texts, thus averting translation errors and communication barriers. With this in mind, this paper offers a brief analysis of the application of context integration in English language learning, aiming to provide readers with valuable insights.

Implementation of Neural Machine Translation in Translating from Indonesian to Sasak Language

Language translation is part of Natural Language Processing, also known as Machine Translation, which helps the process of learning foreign and regional languages using translation technology in sentence form. In Lombok, there are still people who are not very fluent in Indonesian because Indonesian is generally only used at formal events. This research aimed to develop a translation model from Indonesian to Sasak. The method used was the Neural Machine Translation with the Recurrent Neural Network - Long Short Term Memory architecture and the Word2Vec Embedding with a sentence translation system. The dataset used was a parallel corpus from the Tatoeba Project and other open sources, divided into 80% training and 20% validation data. The result of this research was the application of Neural Machine Translation with the Recurrent Neural Network - Long Short Term Memory algorithm, which could produce a model with an accuracy of 99.6% in training data and 71.9% in test data. The highest ROUGE evaluation metric result obtained on the model was 88%. This research contributed to providing a translation model from Indonesian to Sasak for the local community to facilitate communication and preserve regional language culture.

Improving neural machine translation by word translations

Transformer-based neural machine translation (NMT) models have achieved state-of-the-art performance in the machine translation paradigm. These models learn the translation knowledge from the bilingual corpus through the attention mechanism automatically. This differs from the way human translators approach sentence translation, where prior knowledge plays a significant role. Inspired by this, a word translation augmentation (WTA) method is proposed to improve the Transformer-based NMT model. The main steps are as follows: Firstly, constructing the word alignment rules based on the training set. Next, generating the translation rules for source words according to the word alignment rules. Lastly, incorporating the potential translation candidates for each source word into the NMT model during the training and testing procedure. In addition, the WTA method introduces the idea of Mixup for translation candidates of a source word and employs two augmentation strategies to augment the encoder. The results of experiments on several translation tasks with high-resource and low-resource indicate the effectiveness of the proposed method compared with the corresponding strong baseline, and the improvement in BLEU score achieved ranges from 0.42 to 0.63.

Using Symmetries to Lift Satisfiability Checking

We analyze how symmetries can be used to compress structures (also known as interpretations) onto a smaller domain without loss of information. This analysis suggests the possibility to solve satisfiability problems in the compressed domain for better performance. Thus, we propose a 2-step novel method: (i) the sentence to be satisfied is automatically translated into an equisatisfiable sentence over a ``lifted'' vocabulary that allows domain compression; (ii) satisfiability of the lifted sentence is checked by growing the (initially unknown) compressed domain until a satisfying structure is found. The key issue is to ensure that this satisfying structure can always be expanded into an uncompressed structure that satisfies the original sentence to be satisfied. We present an adequate translation for sentences in typed first-order logic extended with aggregates. Our experimental evaluation shows large speedups for generative configuration problems. The method also has applications in the verification of software operating on complex data structures. Our results justify further research in automatic translation of sentences for symmetry reduction.

Analisis Kesalahan Bahasa Arab dalam Penulisan Karya Ilmiah

The writing of this article departs from the problem of some students who have errors in applying the nahwu-shorof rule in writing perfect sentences in Arabic articles that have compatibility between nahwu-shorof or the selection of appropriate sentences. This qualitative description research analyzes errors in the application of Arabic rules in PBA UNWAHA student articles. Through observations of 5 random Arabic articles of PBA UNWAHA students from across years, researchers can approach error analysis by identifying errors, classifying errors, describing errors, and analyzing the factors that cause errors based on linguistic phenomena that appear in Arabic articles of PBA UNWAHA students. The results of this study showed that overall, there were 60 errors from the 5 articles. The data showed that of the 5 articles, 36.7% experienced errors in choosing appropriate sentences, 53.3% experienced errors in compatibility between mudzakkar-muannats, and the remaining 10% experienced errors in the aspect of i'rob. The factors causing the error are linguistic and social. To avoid language errors, students must focus more on Arabic rules, be careful in the translation and selection of appropriate sentences, and apply sentence analysis before publishing articles to apply the theory and practice of applying Arabic rules.

A study on intelligent translation of English sentences by a semantic feature extractor

Abstract In order to enhance the performance of machine translation, this article briefly introduced algorithms that can be used to extract semantic feature vectors. Then, the aforementioned algorithms were integrated with the encoder–decoder translation algorithm, and the resulting algorithms were subsequently tested. First, the performance of the semantic recognition of the long short-term memory (LSTM)-based semantic feature extractor was tested, followed by a comparison with the translation algorithm that does not include semantic features, as well as the translation algorithm that incorporates convolutional neural network-extracted semantic features. The findings demonstrated that the LSTM-based semantic feature extractor accurately identified the semantics of the source language. The proposed translation algorithm, which is based on LSTM semantic features, achieved more accurate translations compared to the other two algorithms. Furthermore, it was less affected by the length of the source language.

Machine translation: Turkish–English bilingual speakers’ accuracy detection of evidentiality and preference of MT

Machine translation (MT) is the automated process of translating text between different languages, encompassing a wide range of language pairs. This study focuses on non-professional bilingual speakers of Turkish and English, aiming to assess their ability to discern accuracy in machine translations and their preferences regarding MT. A particular emphasis is placed on the linguistically subtle yet semantically meaningful concept of evidentiality. In this experimental investigation, 36 Turkish–English bilinguals, comprising both early and late bilinguals, were presented with simple declarative sentences. These sentences varied in their evidential meaning, distinguishing between firsthand and non-firsthand evidence. The participants were then provided with MT of these sentences in both translation directions (Turkish to English and English to Turkish) and asked to identify the accuracy of these translations. Additionally, participants were queried about their preference for MT in four crucial domains: medical, legal, academic, and daily contexts. The findings of this study indicated that late bilinguals exhibited a superior ability to detect translation accuracy, particularly in the case of firsthand evidence translations, compared to their early bilingual counterparts. Concerning the preference for MT, age of acquisition and the accuracy detection of non-firsthand sentence translations emerged as significant predictors.

English Translation of Long and Difficult Sentences from the Perspective of Analytic Interpretation Theory: An Example of Political Texts

Long and difficult sentences, is the key to text comprehension. It is committed to foster the apprehension based on quick in uptake of English difficult sentences in translation process for translators referring to applying the three links of the paraphrase theory triangle model to analyze the sentence structure of difficult sentences, including component repetition, and cultural differences in difficult sentences. For the sentence to be taking the situation light on appropriate theoretical guidance, systematic analysis and specific ways, the thesis endeavors to conduct a cognitive study in the length and difficulty definition, and divides the sentences following the definition into two types, “V + type” and “A + type”, to carry out a comparative analysis of the predicate part, supplemented by a comparative analysis in the Interpretative Triangle Model. Through comparative analysis, the fuzzy process of the appearance ignored the precise forms is made to supplement, that provides inspiration and methods for exploring the optimal solution of English translation in Long and difficult sentences.

Syntactic Iconicity in English-Chinese Translation of Complex Sentences in Energy Texts

Syntactic Iconicity in English-Chinese Translation of Complex Sentences in Energy Texts

Semantic Accuracy and Cultural Adaptability in the English-Chinese Translation of Jane Eyre Based on Computational Linguistics and Natural Language Processing Techniques

Abstract This paper takes Jane Eyre as an example to study the role of computational linguistics and natural language processing technology on the semantic accuracy and cultural adaptability of English-Chinese translation. We construct an interactive translation system of Jane Eyre, based on the interactive translation model design of computational linguistics and natural language processing technology, to support the application of these technologies in the English-Chinese translation of Jane Eyre. Context-association mapping, semantic retrieval, and semantic ontology structural feature construction methods are employed to evaluate semantic accuracy and cultural adaptability. We empirically analyze the semantic accuracy and cultural adaptability of the English-Chinese translation of Jane Eyre using text data from a Python web crawler. The results show that the semantic accuracy of the English-Chinese translation of Jane Eyre in this paper’s model is the highest compared to SAN (self-attention network) and RNN (recurrent neural network) translation models. Among the 200 students sampled, the translation result achieved a satisfaction rate of 71.5%. The work’s translation of literary sentences is more in line with the effect of Chinese expression, indicating excellent cultural adaptability.

A Study on the Practical Application of Computational Modeling in Culturally Adaptive Teaching in the Reform of Translation Teaching in Colleges and Universities

Abstract Language is the bridge of communication between people. Different countries or regions have different social backgrounds, languages, and so on, so cultural differences must be paid attention to in the translation process. This paper focuses on exploring ways to improve students’ culturally adaptive translation ability during translation teaching. The particle swarm algorithm is employed to enhance the calculation model and create the analysis model for students’ culturally adaptive translation ability. The model is trained in Matlab software, and the correlation between the expected value and the measured value is measured by regression analysis to test the model’s performance. Subsequently, the model of this paper was applied to teaching practice, an experimental class was set up, a parallel control class was selected for reference, and a comparative analysis of the students’ culturally adaptive translation ability was conducted before and after the experiment in order to verify the effect of the application of the model of this paper on the improvement of the students’ culturally adaptive translation ability. The average score of students in the experimental class increased by 34.78% before and after the experiment, and the average score of students in the experimental class increased by 19.23% compared with that of students in the control class after the experiment. Compared to the pre-experiment, the increase in the scores of the students in the two classes for the culturally adaptive translation of long and difficult sentences was 116.67% and 47.62%, respectively.

A Study of Business English Translation Skills Based on Parallel Corpus

Abstract In this paper, the support vector machine is used as the overall classification of the paragraph alignment method. The paragraph length relationship is taken as an essential feature of the business English paragraph alignment model, the CRFs discriminative model is used as the word alignment task model, and the maximum likelihood estimation algorithm is used for model parameter training. Aiming at the real-time alignment needs at the sentence or paragraph level in Business English, the word alignment algorithm based on semantic similarity calculation is proposed, and the evaluation indexes of English-Chinese EC, Chinese-English CE unidirectional alignment and bi-directional fusion alignment, and semantic extension alignment are compared. Adding traditional business English translation techniques, comparing the effects of conventional translation techniques on business English sentence and paragraph translation versus parallel corpus-based translation techniques. The dynamic chunking accuracy of two-way fusion alignment and semantic expansion alignment is 94.57% and 94.32%, respectively, and the accuracy of semantic expansion alignment is 6.85% and 8.17% higher than that of EC one-way alignment. Meanwhile, the number of errors in business English translation works based on parallel corpora is reduced, which can help translators overcome the interference of Chinese chapter structures and improve the quality of their translation works.

The Construction of “Interactive” English Translation Teaching Mode in the Background of Internet

Abstract This paper discusses the construction of “interactive” English translation teaching mode in the background of the Internet, and analyzes the application of neural machine translation model in improving the effect of translation teaching. The research adopts Word2vec algorithm to train word vectors, combines neural network language model and encoder-decoder structure, and constructs Transformer model and CNN+Transformer model to improve translation efficiency and quality. The translation experiments on sentences of different lengths show that the models perform better in short sentence translation. The experimental results show that the proposed model outperforms the traditional model in terms of BLEU value, and the best translation effect is found in test set 1, where the BLEU value is improved by 10.6 and 11.7 compared with that of the baseline model and the CNN model, respectively. The “interactive” teaching mode designed with POA theory significantly outperforms the traditional teaching mode regarding students’ lexical, grammatical and semantic translation quality. The “interactive” English translation teaching with neural translation model can effectively improve the quality of translation teaching and students’ learning effect.