scholarly journals Networked Artificial Intelligence English Translation System Based on an Intelligent Knowledge Base and Translation Method Thereof

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Shuping Ren
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Base ◽  
Structure Analysis ◽  
English Translation ◽  
Language Translation ◽  
Translation Method ◽  
Translation System ◽  
Chinese Translation ◽  
Lexical Structure ◽  
Traditional Language

Language translation is often conducted in work and study. Traditional language translation is based on lexical structure analysis. However, natural language is not so standardized, which causes this translation method to have fundamental defects, no matter how much the algorithm is improved. The translation results and human translation will be very different. This paper mainly studies the networked artificial intelligence. The English translation system and translation methods are based on a smart knowledge base. Bringing an example of English-Chinese translation to suggest translations according to the intelligent knowledge base explains in detail the principle of intelligent knowledge-based translation and the advantage of this translation method compared with the traditional translation method based on lexical structure analysis. In the experiment of this paper, when the variance is 2/N, 30/N, 100/N, and 2N, it is the experimental data for an in-depth study. When the variance is 2/N, 30/N, and 100/N, the result is the same as that when the variance is 0.5; the result when the variance is 2N also conforms to the trend in the tables, which is close to the effect of the smoothing algorithm, which verifies the effectiveness of the system in this paper.

scholarly journals Application of Feature Extraction Algorithm in the Construction of Interactive English Chinese Translation Mode

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Guangjun Dong ◽  
Youchao Yang ◽  
Qiankun Zhang
Keyword(s):  
Feature Extraction ◽  
English Translation ◽  
Selection Process ◽  
Translation System ◽  
Chinese Translation ◽  
Feature Extraction Algorithm ◽  
Extraction Algorithm ◽  
Optimal Feature Selection ◽  
Translation Accuracy ◽  
Optimal Feature

In the process of English translation, traditional interactive English translation system is not obvious in English semantic context. The optimal feature selection process does not achieve the optimal translation solution, and the translation accuracy is low. Based on this, this paper designs an interactive English Chinese translation system based on a feature extraction algorithm. By introducing the feature extraction algorithm, the optimal translation solution is selected, and the semantic mapping model is constructed to translate the best translation into English Chinese translation. The real experiment results show that the interactive English Chinese translation system based on feature extraction algorithm can get the best solution.

Intelligent system for English translation using automated knowledge base

2020 ◽  
Vol 39 (4) ◽  
pp. 5057-5066
Author(s):  
Shengqin Bi
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Base ◽  
Machine Translation ◽  
English Translation ◽  
Experimental Simulation ◽  
K Value ◽  
Artificial Intelligence Technology ◽  
Hybrid Recommendation ◽  
Very High

In the process of globalization, machine translation has undergone a long period of evolution and development. Although the development level of machine translation has been greatly improved, the quality of machine translation is still not very high, and it is difficult to meet the needs of users. Artificial intelligence is the science that studies the laws of human intelligent activity. The application of artificial intelligence technology in the English depression and depression, combined with the Internet and intelligent knowledge base, can develop English translation systems to solve the problem of English translation to a certain extent. Based on the above background, the research content of this article is a neural network-based artificial intelligence technology English translation system based on the intelligent knowledge base. This article is mainly based on the existing English-Chinese machine translation to find a more favorable method for English long sentence translation. By improving part-of-speech tagging and rules, the rules can match more sentence patterns to improve the quality of existing machine translations. This paper proposes an improved hybrid recommendation algorithm, and through experimental simulation, the results show that the accuracy of the algorithm is not very high. The highest is 35.64%. The possible reason may be that the k value is selected during k-means text clustering, or the N value recommended by TopN is not selected properly, but the hybrid recommendation is still better than ordinary collaborative filtering.

scholarly journals Research on Business English Translation Architecture Based on Artificial Intelligence Speech Recognition and Edge Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yunwei Xu
Keyword(s):  
Artificial Intelligence ◽  
Speech Recognition ◽  
News Media ◽  
English Translation ◽  
Chinese Culture ◽  
Online News ◽  
Edge Computing ◽  
Target Language ◽  
Translation System ◽  
Business English

In today’s society, the continuous deepening of international cultural integration has become the background of the times. China has become more and more closely connected with the world, and many physical or online news media have become a platform for China to receive world information and spread Chinese culture. Business English translation is therefore valued by translation researchers and translators. Aiming at the shortcomings of current business English translation research, this paper designs and develops a business English translation architecture based on artificial intelligence speech recognition and edge computing. First of all, considering the relevance and complementarity between speech and text modalities, this paper uses the deep neural network feature fusion method to effectively fuse the extracted monomodal features and perform speech recognition. Secondly, adopt the edge computing method to establish the business English translation system architecture. Finally, the simulation test analysis verifies the efficiency of the business English translation framework established in this paper. Compared with the existing methods, our proposal improved the accuracy than others at least 10% and the time of model building also decreased obviously. The purpose of this research is to discuss how to deal with the many differences between the source language and the target language, and how to enhance the readability of the translation and meet the reader’s cultural cognition and needs.

Research on language analysis of English translation system based on fuzzy algorithm

2020 ◽  
pp. 1-9
Author(s):  
Zhiqian Yuan ◽  
Chaoyang Jin ◽  
Zhaojun Chen
Keyword(s):  
Image Recognition ◽  
English Translation ◽  
Rapid Development ◽  
Language Translation ◽  
Translation System ◽  
Fuzzy Algorithm ◽  
Language Analysis ◽  
Gaussian Blur ◽  
Language Characteristics ◽  
Translation Accuracy

In recent years, with the rapid development of computer technology, the need for barrier-free communication between people of all countries have become more and more urgent. Therefore, it is extremely important to establish a high translation accuracy and high-quality English translation system. At present, Although the various English translation systems on the market have solved the communication problems between different languages to a certain extent, there are a series of problems such as language translation ambiguity and inaccurate use of words in translation methods, in order to improve English The translation accuracy of the translation system can improve the quality of the English translation system. This paper proposes a language analysis study of the English translation system based on fuzzy algorithms. The research of this paper firmly grasps the analysis and understanding of the language, analyzes it from the corpus, vocabulary, syntax, and translation characteristics, and fully understands its language characteristics, so as to eliminate the semantic understanding ambiguity in the translation process to a certain extent. Thereby improving the accuracy of the translation. The English translation system designed in this paper includes an image input module and an image recognition module, so the Gaussian blur algorithm is used for processing. The Gaussian blur algorithm can retain edge information in the edge area where the pixel value of the image changes sharply, and can effectively remove noise and enhance the image effect. Therefore, this article uses fuzzy algorithm-based English translation system language analysis research, first analyze the English language characteristics, and then use Gaussian fuzzy algorithm to denoise the image in the translation system, and then display the image recognition results.

A spoken language translation system

1992 ◽  
Author(s):  
Tsuyoshi Morimoto ◽  
Masami Suzuki ◽  
Toshiyuki Takezawa ◽  
Gen'ichiro Kikui ◽  
Masaaki Nagata ◽  
...  
Keyword(s):  
Language Translation ◽  
Spoken Language ◽  
Translation System ◽  
Spoken Language Translation

Research on Machine Translation Technology in English Translation Process

2014 ◽  
Vol 687-691 ◽  
pp. 1210-1213
Author(s):  
Ke Tian
Keyword(s):  
Machine Translation ◽  
English Translation ◽  
Development Process ◽  
Translation System ◽  
Translation Process ◽  
Sentence Meaning ◽  
Cultural Exchanges ◽  
Response Measures ◽  
World Economic ◽  
Translation Machine

Translation plays an important role in the world economic and cultural exchanges. Translation is divided into machine translation and human translation, which is complement each other in promoting world economic and social development process. In this paper, Collaborative Translation gets much attention, along with the growth of collaborative translation, English translation technology also towards a new milestone, the characteristics of collaborative translation process and scientific literature are briefly introduced, and collaborative translation technology English Translation applications made a brief explanation. From the perspective of the development of machine translation, comparative analysis of the characteristics of human translation machine translation strengths and weaknesses, and we make relevant response measures and selection criteria translation approach. The specific translation system is analyzed from the perspective of textual and the Collaborative Translation shortcomings, as well as interpretation of collaborative translation features, functions and its impact on the meaning and sentence meaning.

scholarly journals A Belief Update System Using an Event Model for Location of People in a Smart Home

2021 ◽  
pp. 17-32
Author(s):  
Marie Bernert ◽  
Fano Ramparany
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Base ◽  
Smart Home ◽  
Current Knowledge ◽  
Sequence Of Events ◽  
New Information ◽  
Event Model ◽  
Location Inference

AbstractArtificial Intelligence applications often require to maintain a knowledge base about the observed environment. In particular, when the current knowledge is inconsistent with new information, it has to be updated. Such inconsistency can be due to erroneous assumptions or to changes in the environment. Here we considered the second case, and develop a knowledge update algorithm based on event logic that takes into account constraints according to which the environment can evolve. These constraints take the form of events that modify the environment in a well-defined manner. The belief update triggered by a new observation is thus explained by a sequence of events. We then apply this algorithm to the problem of locating people in a smart home and show that taking into account past information and move’s constraints improves location inference.

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