


































Education, Language and Sociology Research 

ISSN 2690-3644 (Print) ISSN 2690-3652 (Online) 

Vol. 3, No. 4, 2022 

www.scholink.org/ojs/index.php/elsr 

43 
 

Original Paper 

On the Translation Strategies of Human-computer Interaction 

Based on Machine Translation 

QIN Fangfang1 & XIANG Xiaomei2* 

1 School of Foreign Languages of China Three Gorges University, Yichang City, Hubei Province, China  

2 College of Humanities and Social Sciences of Xinjiang Institute of Technology, Aksu, Xinjiang, China 

* XIANG Xiaomei, College of Humanities and Social Sciences of Xinjiang Institute of Technology, Aksu, 

Xinjiang, China 

 

Received: September 13, 2022     Accepted: October 1, 2022    Online Published: October 20, 2022 

doi:10.22158/elsr.v3n4p43           URL: http://dx.doi.org/10.22158/elsr.v3n4p43 

 

Abstract 

With the rapid development of language service industry and artificial intelligence technology, machine 

translation plays a more prominent role in the translation industry. Human-computer interaction 

translation greatly improves the speed and quality of translation, and pre-translation editing and post-

translation editing are two important links and manifestations in human-computer interaction 

collaborative translation. On the basis of summarizing machine translation problems, this paper 

proposes translation strategies including replacing well-translated terms in advance, rewriting, addition, 

omission, and shift via pre-editing and post-editing, which greatly improves the quality of machine 

translation. 

Keywords 

human-computer interaction translation, machine translation, pre-editing, post-editing 

 

1. Introduction 

From the beginning of the 21st century, machine translation technology has developed rapidly in China. 

Faced with the surge in market demands for language services, human translation or pure machine 

translation can no longer meet these needs. In recent years, with the emergence of neural network 

machine translation and the “machine translation + post-translation editing” model, the quality and 

efficiency of translation have been greatly improved, but there is still a certain gap compared to 

professional human translation. So, how to further innovate on the basis of machine translation? In other 

words, what else can we do to improve machine translation? In view of this, based on summarizing 

machine translation problems, the author proposes the “pre-translation editing + machine translation + 

post-translation editing” model, and concludes a series of translation strategies from pre-translation 



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editing and post-translation editing, thus providing a certain reference for future human-computer 

interaction translation research and application. 

 

2. Research Status 

The study of how to use computers to automatically convert natural languages is one of the important 

research fields in artificial intelligence and natural language processing. As a key technology to break 

through the language barrier by information transmission between different countries and ethnic groups, 

machine translation is of great significance for promoting ethnic unity, strengthening cultural exchanges 

and promoting foreign trade (Liu, 2017, p. 1144). 

In the 17th century, Descartes and Leibniz proposed the idea of using machine dictionaries to overcome 

language barriers. IBM’s 701 computer automatically translated 60 Russian sentences into English, the 

first machine translation in history. Machine translation has experienced a long and tortuous development 

process, which is generally divided into the following four stages: the inception period (1949-1960), the 

setback period (1960-1967), the recovery period (1967-1990) and the new period (1990-present) (Gao & 

Zhao, 2020, pp. 97-98). 

Although the quality of machine translation has increased, it is still not comparable to high-quality human 

translation. Pure machine translation cannot guarantee the translation quality, let alone meet the 

increasing demand for language services. Therefore, the function of human-computer interaction 

translation has become increasingly prominent with the pre-editing and post-editing as its important 

manifestations. “Pre-translation editing is mainly aimed at the source text. It refers to the targeted 

modification and editing of the texts or documents that need to be translated before machine translation 

to improve the quality of machine translation output, and post-translation editing means to modify and 

edit the original output of machine translation. Its purpose is also to improve the quality of machine 

translation through human-machine interaction” (Feng & Gao, 2017, p. 63). 

At present, in-depth research on machine translation has been carried out in China. Post-translation 

editing is also a new hot research topic. The post-translation editing is an important manifestation of 

human-computer interaction, a new business growth point for language service companies, and the 

development direction of translation services in the future (Cui, 2014, p. 70). At the same time, the 

research on pre-translation editing has not been fully carried out. Some researchers believe that the 

advantages of pre-translation editing are not obvious, and there are defects such as large workload and 

low efficiency. However, the author believes that proper pre-editing can increase the quality and 

acceptability of machine translation. Moreover, the enthusiasm of scholars for pre-translation editing has 

gradually increased in recent years, and a series of researches have been carried out around it. It can be 

clearly found out from CNKI data that the number of related journals published about pre-translation 

editing since 2018 has increased year by year. Therefore, the author proposes the “pre-translation editing 

+ machine translation + post-translation editing” model, hoping to improve the machine’s understanding 

of the source text to reduce the workload of post-translation editing, and promote translation efficiency 



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through pre-translation editing. However, even after pre-editing and machine translation, there are still 

some problems in the translation, and in this case, post-editing is necessary. 

 

3. Common Problems of Machine Translation 

Although machine translation has greatly improved translation efficiency, there are also some 

unavoidable problems in its original output, which make the translation quality unsatisfactory, such as 

follows: 

3.1 Terms Inconsistency 

A term is used to express the exact concept of a particular thing. The “inconsistency of terms” means in 

the process of translation, namely, conversion from the source language to the target language, one term 

of the source language has different expressions, but the multiple expressions in the source text for the 

same thing are translated into different versions in the target text by machine. The difficulty for computer 

to analyze Chinese language lies in the fact that the same part of speech in Chinese serves as multiple 

grammatical components without morphological changes, and the formation principles of Chinese 

sentences are basically the same as those of phrases (Guo & Wang, 2017, p. 78). Especially for large 

texts, it is prone to cause terms inconsistency by machine translation because of the context or the 

different collocations of the same term.  

3.2 Improper Segmentation of Punctuation Marks 

Punctuation marks are an integral part of a written language. At present, the punctuation marks used in 

Chinese are formulated based on the English punctuation system. They do not only retain most of the 

main characteristics of English punctuation, but also shows the characteristics of Chinese language. 

Therefore, there are some differences between Chinese and English punctuation marks, which are a major 

cause of the difference in sentence structure and expression between Chinese and English. But the 

importance of punctuation is often overlooked in machine translation. For example, book titles and 

commas are punctuation marks which are unique to Chinese. During the process of Chinese-English 

conversion, machine translation will copy them into the target text, resulting in some translation problems. 

3.3 Redundancy 

Redundancy refers to the functional repetition, overlapping or redundant expressions in the translation 

(Cui & Li, 2015, p. 21). Repetition is a typical feature of Chinese, and synonymy with different words in 

the form of four-character words is very common for emphasis. But English avoids repetition and often 

uses alternatives such as pronouns and prepositions to replace the repeated part. In the process of machine 

translation, the machine will strive to translate all the content of the source language, which is alien with 

English expression habits.  

3.4 Lexical Vacancy 

Lexical vacancy refers to the difficulty in achieving complete equivalence between the source language 

and the target language, resulting in lexical vacancy in translation. Due to differences in culture and social 

background between China and other countries, lexical vacancy occurs in the translation process, 



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including cultural defaults during the translation of culture-loaded words. Moreover, in the ever-changing 

modern society, in addition to new words emerging with the development of the times, many old words 

have also been given new meanings, such as “韭菜” ( it once meant a kind of vegetables, and now also 

refers to shareholders taking a beating) and “香菇” (it once meant a kind of vegetable, and now also 

refers to a state of sadness). Therefore, if the lexical vacancy cannot be solved, the translation quality 

cannot be guaranteed. Because the society is changing so fast that the original database of machine cannot 

keep up with the pace, or the research on the cultural differences is not sufficient, the machine translation 

cannot accurately detect the meaning of the source text, which will lead to such translation problems. 

 

4. Translation Strategies  

The above-mentioned problems could be solved by adopting translation techniques including replacing 

the inconsistent terms in source text and adjusting the division of sense group in pre-translation editing, 

as well as addition, omission and shift in post-translation editing. 

4.1 Translation Strategies from the Perspective of Pre-editing 

There are differences between Chinese and English languages. Chinese is featured with run-on sentences, 

four-character words, and implicit subjects. At the same time, it stresses on parataxis with more active 

sentences. English is featured with complex and long sentences, as well as explicit subjects, and attaches 

importance to hypotaxis. One of the main tasks of pre-editing Chinese is to eliminate the ambiguity of 

the source text, that is, to convert human-comprehensible words and sentences into machine-

comprehensible ones (Zhong, Xu, & Li, 2021, p. 36). Therefore, this section focuses on pre-translation 

editing from the aspects of replacing the well-translated terms and modifying punctuation marks so as to 

solve term inconsistency and incorrect punctuation mark segmentation. 

4.1.1 Replacing the Inconsistent Terms in Source Text 

Although machine translation has powerful memory and terminology functions, it is not a panacea. 

Chinese culture has a long history, and neologisms emerge endlessly on the Internet. The computer 

storage function is not nearly enough to catch up with their development and evolution. Faced with some 

specific words, especially those with cultural connotations or implied meanings which are not included 

in the given glossary, machine translation cannot understand and translate correctly. In this case, words 

in the source language can be replaced in advance through pre-translation. Besides, affected by the 

context, there will be inconsistent terms in machine translation, which weakens the coherence and 

cohesion of the translated text. If the expression of the same term is inconsistent, it also will increase the 

reading difficulty of readers, and may even cause misunderstanding. In view of this, the translation and 

replacement of inconsistent terms in advance can improve the consistency and the quality of machine-

translated text. Moreover, after the terminology is established, it can also provide reference for future 

texts with similar topics. 



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By replacing the inconsistent terms in source text, the whole text is unified, so that the language and 

expression of the machine-translated text are more natural and fluent, which not only improves the quality 

of the translated text, but also reduces the workload of post-translation editing.  

4.1.2 Adjusting the Division of Sense Group 

Adjusting the division of sense group refers to various adjustments such as changing, deleting, editing, 

and omitting the source text, in order to meet the requirements of the “patron” mainstream social ideology 

(Yi & Liu, 2021, p. 4). Due to the inherent characteristics of Chinese, such as run-on sentences and four-

character words, it is inevitable to cause difficulties including structural ambiguity in the process of 

machine translation. Therefore, it is necessary to analyze the original text and try to adjust the division 

of sense group that is difficult for machine recognition in the source text, so as to improve machine 

translation’s recognition ability of the source text and improve translation quality.  

There are differences between Chinese and English punctuation marks. For example, some punctuation 

marks in Chinese are not found in English, such as stops and book titles; some punctuation marks in 

English are not found in Chinese, such as hyphens; most punctuation marks are both used in Chinese and 

English, but their usages are slightly different. In the process of machine translation, the machine 

translates the text according to the arrangement and structure of punctuation marks in the original text, 

resulting in “deficient” or “repetitive” translation. In such cases, modifying punctuation marks and 

reforming sentence structure can change the source text into a language that is easier to understand and 

translate by the machine, thus improving the readability of the text. 

Punctuation marks are an indispensable part of a written language, mainly used to indicate the nature and 

function of sentences (Yuwen, 2001, p. 76). It is also a detail that is easy to be ignored in the translation 

process, but it reflects the translator’s ability of avoiding “stupid mistakes” and the level of professional 

qualification. In addition, the modification of punctuation marks is also an important aspect of pre-

translation editing. This is similar to the text alignment function of many computer-aided translation tools 

such as Trados, but text alignment is to manually segment the machine-translated target language 

translation and the source language, rather than better modify the source language text to make machine 

translation more recognizable.  

4.2 Translation Strategies from the Perspective of Post-editing 

Post-translation editing refers to the process of modifying the source output of machine translation for 

certain purposes (Feng & Cui, 2016, p. 67). Liu Yi stresses that no matter how intelligent the machine is, 

and no matter how long the translator spends on pre-translation editing, the texts that are not successfully 

translated still account for a certain proportion (Liu, 2014, p. 101). At present, for the gap between 

professional human translation and machine translation, we cannot rely on machine translation alone, 

thus post-translation editing is also required. No matter the language expressions are familiar or not, it is 

still difficult to achieve the prefect translation result, so post-translation editing is of great importance 

(Yang & Fan, 2021, p. 59). Thus, the author puts forward translation skills such as addition, omission 

and shift to improve the accuracy and quality of machine translation.  



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4.2.1 Omission 

Omission refers to a method of removing redundant information in translation and making the translation 

more fluent (Wang & Wen, 2020, p. 134). It is not simply to delete the content, but to do some meaningful 

deletion avoiding repetition and redundancy. The meaning is still complete after deletion, but the 

expression is more concise. In order to achieve neat writing, Chinese often uses a large number of 

balanced and parallel structures and a string of four-character sentences. But English is concise and 

avoids repetition. Therefore, in the process of Chinese-English translation, repetitive problems will 

inevitably occur, and omission can effectively reduce the redundancy to make the edited language more 

suitable for English expression habits. 

4.2.2 Addition 

Addition refers to the appropriate addition to the translated text, so that it not only faithfully expresses 

the content of the source text, but also conforms to the expression habits of the target language. In 

Chinese-English translation, addition includes the amplification of pronouns, background knowledge and 

subjects. The text translated by machine is right sometimes, but the machine fails to fully take into 

account the knowledge reserves of the target language readers. With supplementary information, it can 

not only better convey the original information, but also reduce the barriers that appear in cultural 

exchanges. For example, in the past, Chinese culture may belong to the “weak culture”, and the 

translation of classic books mainly adopts the strategy of “domestication”. However, as Chinese culture 

is increasingly prosperous, translators who are familiar with the similarities and differences of the two 

languages and cultures (Zhang, 2010, p. 26) should shoulder the responsibility of helping Chinese culture 

“going global”, so that more people can understand the excellent traditional Chinese culture.  

In addition, translation skills such as adding footnotes, paraphrasing, or adding direct annotations can 

make up for the default of the culture-loaded words. Culture-loaded words, also known as culture-specific 

words, refer to the characteristic words (including idioms and common sayings) that carry a certain 

cultural connotation and show folk customs, which are often concentrated in national cultural works (Sun 

& Han, 2021, p. 91). It is this exclusivity that makes it a big obstacle in translation. In the process of 

translation, rigid translation will damage readability, and the practice, “completely change” will make it 

lose its original taste. Therefore, the author should strive to reduce cultural differences while enhancing 

readers’ reading experience and cognitive ability.  

4.2.3 Shift 

Shift refers to the process of converting the language unit or structure of the original language into a 

language unit or structure with similar properties, or corresponding properties, or heterogeneous 

properties in the target language (Xiong, 2014, p. 87). Simply put, it is to change the form of expression 

to a certain extent, but the original meaning remains unchanged. When “hard translation” or “rigid 

translation” occurs in machine translation, this translation strategy can be adopted. For example, when 

translating dialects, idioms, and folk songs, the machine cannot understand the cultural connotations in 

them, but often translate word by word, making the entire text incomprehensible. In view of this, these 



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translation difficulties are manually converted into expressions that are familiar to the target language 

readers and easy to understand.  

Machine translation has always been a hot topic in translation circles at home and abroad, and has high 

requirements on the ability of researchers themselves. The author finds that machine translation has 

difficulties in cultural factors such as beliefs and customs mainly because it fails to understand the 

cultural context and emotions conveyed in the text. The biggest difference between human and machine 

is the feelings. The translators will consider the differences and taboos of different cultures and the 

reaction and mood of the target language readers, rather than simply complete the translation task. 

Therefore, in order to promote the successful exchange between Chinese and foreign cultures, post-

translation editing is also indispensable. 

 

5. Conclusion 

With the progress of science and technology and the continuous development of artificial intelligence, 

machine translation has attracted more attention. It is faster and cheaper than human translation, and can 

handle huge volumes of multilingual text. However, machine translation lacks logical thinking, which 

will make the translation lack of logic and standardization, thus leading to ambiguity, or even distortion 

of the source text. The “pre-editing + machine translation + post-editing” model gives full play to the 

advantages of the interactive cooperation between human and machine by replacing the inconsistent 

terms in source text and adjusting the division of sense group in pre-editing part which improves the 

translatability of the text, and increasing the readability of the translation by addition, omission and shift 

in post-editing, both greatly improve the translation quality and have strong operability. 

 

Acknowledgements 

This work was supported by the Postgraduate Course Construction Fund of China Three Gorges 

University in 2022 (No.SDKC202212) and the Teaching and Research Fund of China National 

Committee for Translation & Interpreting Education in 2019 (No. MTIJZW201917).  

 

References 

Cui, Q. L., & Li, W. (2015). The Character of Error Types of Post-editing: Perspective of Machine 

Translation Based on Scientific and Technology Materials. Chinese Science & Technology 

Translators Journal, 28(4), 19-22. 

Cui, Q. L. (2014). On Post-editing in Machine Translation. Chinese Translators Journal, 35(6), 68-73. 

Feng, Q. G., & Cui, Q. L. (2016). Research Focuses and Trends in Post-editing of Machine Translation. 

Shanghai Journal of Translators, 6, 67-74+89+94. 

Feng, Q. G., & Gao, L. (2017). On the Influence of Pre-editing in Accordance with Controlled Language 

on Machine Translation. Contemporary Foreign Language Studies, 2, 63-68+87+110. 



www.scholink.org/ojs/index.php/elsr              Education, Language and Sociology Research              Vol. 3, No. 4, 2022 

50 
Published by SCHOLINK INC. 

Gao, L. L., & Zhao, W. (2020). An Overall Study on Machine Translation. Foreign Languages in China, 

17(6), 97-103. 

Guo, G. P., & Wang, Z. Y. (2017). Research on the Pre-edit and Post-edit of Machine Translation in 

Science and Technology Text Translation. Journal of Zhejiang International Studies University, 3, 

76-83. 

Liu, Y. (2017). Recent Advances in Neural Machine Translation. Journal of Computer Research and 

Development, 54(6), 1144-1149. 

Liu, Y. (2014). Empirical Study of Controlled Language for Improving the Quality of the Machine 

Translation Technical Specifications. Journal of Chongqing University of Technology (Natural 

Science), 28(3), 96-101. 

Mellinger, C. (2017). Translators and Machine Translation: Knowledge and Skills Gaps in Translator 

Pedagogy. The Interpreter and Translator Trainer, 4, 280-293. 

https://doi.org/10.1080/1750399X.2017.1359760 

O’Brien, S. (2006). Methodologies for Measuring the Correlations Between Post-Editing Effort and 

Machine Translatability. Machine Translation, 1, 37-58. https://doi.org/10.1007/s10590-005-2467-

1 

Sun, L., & Han, C. H. (2021). English Translation of Culture-loaded Words in Folding Beijing from the 

Perspective of Eco-translatology. Shanghai Journal of Translators, 4, 90-94. 

Wang, N., & Wen, Y. Y. (2020). On the Translation Problems of Luo Xiwen Version of Shanghanlun. 

Chinese Translators Journal, 41(5), 130-135.  

Xiong, B. (2014). Concept Confusion in Translation Studies: A Case study of “Translation strategies”, 

“Translation methods” and “Translation techniques”. Chinese Translators Journal, 35(3), 82-88.  

Yang, W. D., & Fan, Z. R. (2021). Case Studies of Postediting in Machine Translation of Scientific and 

Technological Texts. Shanghai Journal of Translators, 6, 54-59. 

Yi, X., & Liu, J. P. (2021). On Mistranslation, Rewriting, and Omission in the English Translation of The 

Sky Dwellers. Foreign Language and Translation, 28(1), 1-8+98. 

Yuwen, G. F. (2001). The Difference and Proper Usage of Punctuation Marks in Chinese and English. 

Chinese Journal of Scientific and Technical Periodicals, 12(1), 73-76.  

Zhang, Y. (2010). The Loss and Gain of Interpretation: A Case Study of Amplification in the English 

Translation of Gan Xiao Liu Ji. Contemporary Foreign Language Studies, 4, 26-29+62. 

Zhong, W. M., Xu, J. M., & Li, Y. X. (2021). Pre-editing Mechanisms for Vagueness of Chinese Sci-tech 

Text in Machine Translation. Chinese Science & Technology Translators Journal, 34(4), 36-39+42. 

 

 

https://doi.org/10.1080/1750399X.2017.1359760
https://doi.org/10.1007/s10590-005-2467-1
https://doi.org/10.1007/s10590-005-2467-1

