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With the continuous innovation of computer information technology in our country, its application in our life has attracted a lot of people's attention and love. As we all know, English learning is a process of gradual accumulation. For English majors and non-English majors, the teaching of English translation is very important. The translation software can help them understand the specific meaning of English words or sentences. The application of computer assisted translation software in English translation teaching is the first topic put forward by foreign scientists. It has been proved that the advantages of its application are great. This paper studies and discusses the application of computer assisted translation in English translation teaching, and finally comes to the corresponding conclusion.

With China’s more integration into the process of internationalization, the increasingly close international exchanges and cooperation have provided an unprecedented opportunity for the growth of the translation shop, and the development of the translation shop has provided an unprecedented opportunity for the cultivation of talents. Especially the training of English undergraduate applied translation talents puts forward higher requirements. An excellent translator should not only have good translation ability, but also be good at using new translation techniques to complete translation tasks more efficiently. According to the spirit of the syllabus of English majors in universities, translation course is to cultivate students’ basic ability of writing translation, to conquer the translation abilities of English and Chinese words, long sentences and various styles, and to translate between English and Chinese. At the same time requires accurate and smooth translation of 250-300 words per hour. It has become the goal of more colleges and universities to train senior applied talents with solid English language foundation, skilled translation skills, broad basic theoretical knowledge of international business, good cultural literacy and strong cross-cultural communication skills, and skilled use of English in foreign affairs, trade, culture, education, news media, tourism and other departments engaged in management, translation, foreign trade, international business and foreign tourism. And the current translation course content, the question also can not be underestimated,. The classroom is monotonous, the skill training is not in place, the translation lesson suffers the student’s neglect and the complaint. Therefore, this requires that the English undergraduate translation teaching should be synchronized with the society, change to the social and economic growth, actively explore the practice of computer-aided translation technology, and apply it properly to the English undergraduate translation teaching activities. Try to effectively change the traditional translation practice teaching mode and improve the teaching effect.

With the development of globalization, the contacts and exchanges between countries in the world are getting closer and more frequent. As the most widely used language in the world, English is favored and valued by many non-English speaking countries. In order to facilitate communication, people use computers technology has developed a computer translation tool. The purpose of this article is to explore the difference between machine translation and computer-assisted translation in computer translation, compare the advantages and characteristics of the two in English translation, and point out the direction for future English translation trends. This article uses Google Translator, Youdao Translator and Baidu Translator in machine translation software and Wordfast, WordFisher and iCAT Huoyun Translator in computer-aided translation software as the experimental research objects to compare and analyze the different features and advantages between machine translation and computer-aided translation, and compare the error rate and match rate of the two in English translation. Finally, the experimental results show that the total number of errors in computer-assisted translation software translation is less than that of machine translation software. Among them, WordFisher has the least number of errors, 31 errors in vocabulary, 25 errors in sentences, and 3 errors in punctuation, a total of 59 errors; with the improvement of translation matching rate, the number of translation errors of English professional terminology of machine translation software is increasing, and the error rate is getting higher and higher, when the matching rate is 90-100, Google Translate becomes the software with the most translation errors, and the number of errors reached 78. Studies have shown that computer-assisted English is better and more accurate than machine translation.

Background Despite the popularity of clear aligner treatment, the effect of the thickness of these aligners has not been fully investigated. The objective of this study was to assess the effects of incisor torque compensation with different thicknesses of clear aligner on the three-dimensional displacement tendency of teeth in cases of extraction. Methods Three-dimensional finite element models of the maxillary dentition with extracted first premolars, maxilla, periodontal ligaments, attachments, and aligners were constructed and subject to Finite Element Analysis (FEA). Two groups of models were created: (1) with 0.75 mm-thick aligners and (2) with 0.5 mm-thick aligners. A loading method was developed to simulate the action of clear aligners for the en masse retraction of the incisors. Power ridges of different heights were applied to both groups to mimic torque control, and the power ridges favoring the translation of the central incisors were selected. Then, we used ANSYS software to analyze the initial displacement of teeth and the principle stress on the PDL. Results Distal tipping, lingual tipping and extrusion of the incisors, distal tipping and extrusion of the canines, and mesial tipping and intrusion of the posterior teeth were all generated by clear aligner therapy. With the 0.5 mm-thick aligner, a power ridge of 0.7 mm could cause bodily retraction of the central incisors. With the 0.75 mm-thick aligner, a power ridge of 0.25 mm could cause translation of the central incisors. Aligner torque compensation created by the power ridges generated palatal root torque and intrusion of the incisors, intrusion of the canines, mesial tipping and the intrusion of the second premolar; these effects were more significant with a 0.75 mm-thick aligner. After torque compensation, the stress placed on the periodontal ligament of the incisors was distributed more evenly with the 0.75 mm-thick aligner. Conclusions The torque compensation caused by power ridges can achieve incisor intrusion and palatal root torque. Appropriate torque compensation with thicker aligners should be designed to ensure bodily retraction of anterior teeth and minimize root resorption, although more attention should be paid to the anchorage control of posterior teeth in cases of extraction.

With the rapid development of the times, the role of computer in all aspects of society is becoming more and more obvious, and the translation industry has also been greatly affected. Now the traditional translation no longer meets the requirements of the society, the emergence of computer-supported translation software. Relying on the powerful computing and translation storage functions of computers, translation can be managed more effectively. As a new research field, computer-aided foreign language research has been widely concerned by scholars from all walks of life. Among them, due to its application value, computer-aided translation research has been paid more attention by scholars. Computer assisted translation is computer-assisted translation. The basic operation principle is to search the existing translation language reference room, compare the original text with the translation language group, and select the language materials most similar to the original text. In this paper, through the analysis and understanding of computer-aided translation and its software requirements, as well as the investigation of the current application status and future development forecast, and the understanding of the application defects of computer-aided translation, we can know the operability of computer-aided translation software in practical translation work.

We use reinforcement learning to train an agent for computational RNA design: given a target secondary structure, design a sequence that folds to that structure in silico. Our agent uses a novel graph convolutional architecture allowing a single model to be applied to arbitrary target structures of any length. After training it on randomly generated targets, we test it on the Eterna100 benchmark and find it outperforms all previous algorithms. Analysis of its solutions shows it has successfully learned some advanced strategies identified by players of the game Eterna, allowing it to solve some very difficult structures. On the other hand, it has failed to learn other strategies, possibly because they were not required for the targets in the training set. This suggests the possibility that future improvements to the training protocol may yield further gains in performance.

At present, complete machine translation (MT) cannot meet the needs of information communication and cultural exchange, and the speed of complete human translation is too slow. Therefore, if MT is used to assist in the process of English-Chinese translation, it can not only prove that machine learning (ML) can translate English to Chinese but also improve the translation efficiency and accuracy of translators through human-machine cooperation. The research on the mutual cooperation between ML and human translation has an important research significance for translation systems. An English-Chinese computer-aided translation (CAT) system is designed and proofread based on a neural network (NN) model. First, it gives a brief overview of CAT. Second, the related theory of the NN model is discussed. An English-Chinese CAT and proofreading system based on the recurrent neural network (RNN) is constructed. Finally, the translation accuracy and proofreading recognition rate of the translation files of 17 different projects under different models are studied and analyzed. The research results reveal that according to the different translation properties of different texts, the average accuracy rate of text translation under the RNN model is 93.96%, and the mean accuracy of text translation under the transformer model is 90.60%. The translation accuracy of the RNN model in the CAT system is 3.36% higher than that of the transformer model. The English-Chinese CAT system based on the RNN model has different proofreading results for sentence processing, sentence alignment, and inconsistency detection of translation files of different projects. Among them, the recognition rate for sentence alignment and the inconsistency detection of English-Chinese translation is high, and the expected effect is achieved. The design of the English-Chinese CAT and proofreading system based on the RNN can make the translation and proofreading be carried out simultaneously, which greatly improves the efficiency of translation work. Meanwhile, the above research methods can improve the problems encountered in the current English-Chinese translation, provide a path for the bilingual translation process, and have certain promotion prospects.

The rapid development of science and technology has brought a strong impact on people's traditional habits, among which there is no lack of subversive impact. Even in language communication, the progress of computer technology has been involved and achieved a place. Although computer-aided translation software cannot replace translators to complete translation work independently, it plays an important role in translation work. It not only greatly simplifies the work of translators, lightens the burden for translators, improves their work efficiency, but also helps translators to make faster progress in translation, which can be described as half the result. Through the discussion of the help of computer translation technology, computer aided translation software and computer translation software to translators in translation and learning, as well as the application of computer aided translation technology, the author studies the computer aided translation technology in the background of information age.

With the progress of society and the rapid development of science and technology, computer translation technology has become an important auxiliary tool in the fields of software localization and technical translation. This realistic demand has prompted translators to pay more attention to computer translation and have made some useful explorations on this basis. This paper aims to study and discuss computer-aided translation systems based on the fusion of naive Bayesian algorithms. This paper theoretically analyzes some key technologies in computer-aided translation. Computer-aided translation refers to helping translators to translate texts with a series of tools and then proposes a Bayesian classification algorithm. Translation memory technology can solve many practical problems, especially in the machinery manufacturing industry, processing some sentences in documents, which can reduce repetitive labor, unify vocabulary, and make translation styles more coordinated. The experimental results of this paper show that applying the naive Bayes method to the computer-aided translation system can better classify the documents in the translation system, thereby improving the ability of computer-aided translation. When the proportion of professional terms in the article reaches 85%, computer-aided translation has an auxiliary role for the translator. When the proportion of professional terms in the article reaches about 95%, computer-assisted translation can efficiently speed up the work speed and quality of translators. Due to the prosperity of computer translation systems, the duplication of labor for translators has been significantly reduced, and this ensures the consistency of terminology and translation style, so that the fruits of labor are fully utilized.

The present study aimed to investigate the employment of computer-aided translation (CAT) tools among Iranian freelance translators. Fulford and Granell-Zafra (2005) proposed a model encompassing both information and communications technology (ICT) and CAT tools to support a large number of activities, including document production, information search and retrieval, communications, business management, marketing and work procurement, and translation creation. CAT tools are employed to support document production, business management, and translation creation; and ICT tools are used to support the rest. A questionnaire was used for data collection from Iranian freelancers. As the results indicated, Iranian freelance translators were more interested to employ general-purpose software applications, such as word processing programs and presentation software, whereas they showed less interest in the employment of special-purpose software, such as accounting packages and database software. Moreover, most participants approved the effectiveness of CAT tools in their work.