A Contrastive Analysis of Machine Translation (Google Translate) and Human Translation: Efficacy in Translating Verb Tense from English to Persian

Afshin, Hakiminejad; Alaeddini, Mohammad Ali

doi:10.5901/mjss.2016.v7n4s2p40

Cited by 8 publications

(8 citation statements)

References 3 publications

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“…The number of global monthly users of Google's translation service reached nearly 200 million in early 2012. The text equivalent to 1 million books has been translated, and the translation languages have also been expanded to 62 (12). Interestingly, Google's translation service itself does not have a profit model but based on this, a virtuous circle structure of value is being formed.…”

Section: Translation Servicementioning

confidence: 99%

Philosophical Perspective on the Digital Economy

Lyu¹,

Chen²,

Ko³

et al. 2021

Sci Insigt

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The digital economy is a new economic era and social form of human society after the industrial revolution and information economy. It creates the free time and free activities needed for human development, provides an exploratory plan for the modern society to move toward the sharing economy, and brings many development relations issues that we need to face and examine objectively. From the perspective of human development, this paper deeply discussed the development progress of digital economy through specific cases. We believe that the digital economy breaks the rigid and rational world of humankind based on causality but makes more possible correlations become the philosophical support behind the digital economy model, thereby creating more possibilities for.

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Section: Translation Servicementioning

confidence: 99%

Philosophical Perspective on the Digital Economy

Lyu¹,

Chen²,

Ko³

et al. 2021

Sci Insigt

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“…In order to study the translation efficacy from English into Persian, Afshin and Alaeddini (2016) embarked on a new research in which they analyzed verb tense in Google translation. Their corpus consisted of the Novel Oliver Twist written by Charles Dickens.…”

Section: 2empirical Studies Of the Machine Vs Human Translationmentioning

confidence: 99%

Adequacy in Machine vs. Human Translation: A Comparative Study of English and Persian Languages

Farahani¹

2020

ALR Journal

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Adequacy as the extent to which translation corresponds to the source text has always been a salient feature of any machine translation service. For this reason, the main objective of this comparative study was to analyze and compare translation adequacy in machine vs. human translation from English into the Persian language. In other words, this study sought to investigate whether machine translation product was adequate enough as compared to human translation. For this purpose, seven various texts were selected and translated from Persian to English by two translation students as well as machine translation services including Google Translate and Bing Translation. In addition, a reference translation by two expert translators was prepared against which human and machine translations were compared and analyzed. Moreover, the Sketch Engine software was exploited to analyze the translations. The results of the study revealed that there was no statistically significant difference between human and machine translations as compared to the reference translation and that machine translations were adequately appropriate translations. The findings of this research might have useful implications for research in the field of machine translations. In addition, the results of this research have practical implications for those who are interested in doing research in machine translation.

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“…The auto-generated captioning system that YouTube provides makes use of this technology. Just like voice recognition systems, it is not accurate or free from errors (Afshin & Alaeddini, 2016;Ghasemi & Hasheminan, 2016;Harmeier & Guillou, 2018;Park, 2017;Vidhayasai et al, 2015). However, it is widely used as a useful educational tool in the learning of foreign languages (Bahri & Mahadi, 2016;Lee & Cha, 2019a;Murtisari et al, 2019).…”

Section: Machine Translation Errorsmentioning

confidence: 99%

An Analysis of the Errors in the Auto-Generated Captions of University Commencement Speeches on YouTube

Lee¹,

Cha²

2020

The Journal of AsiaTEFL

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Auto-generated captions on YouTube have proven useful in helping viewers better understand the words being spoken. However, at times they fail to contain accurate captions. In these cases, they lead to confusion. The aim of this paper is to identify and analyze errors in the auto-generated captions of 20 commencement speeches on YouTube. These speeches were presented over a period of 12 years by speakers from different walks of life. The researchers selected ten male and ten female icons. Only the first 10 minutes of the speeches were utilized for this investigation. All the captioned errors were collected and analyzed. Upon completion of the analysis, it was discovered that the frequency of errors in each speech ranged between 10 and 46 cases, with an average of one error occurring about every 26 seconds. Among the different error categories, nouns record the highest number with 144 cases (31.3%). The second is verbs with 93 cases (20.2%), then prepositions with 37 cases (8.1%). Among the four subcategories, namely omission, addition, substitution, and word order, substitution recorded the highest amount of errors with 357 cases (77.6%). Furthermore, the errors were classified into two major groups. The first, involving function words, appeared in 169 cases (36.7%). The second, involving content words, appeared in 291 cases (63.3%). The results of this research suggest that a continuous development of the voice recognition software that automatically generates captions is necessary for more efficient and accurate data that will help viewers and listeners better comprehend the video contents.

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A Contrastive Analysis of Machine Translation (Google Translate) and Human Translation: Efficacy in Translating Verb Tense from English to Persian

Cited by 8 publications

References 3 publications

Philosophical Perspective on the Digital Economy

Philosophical Perspective on the Digital Economy

Adequacy in Machine vs. Human Translation: A Comparative Study of English and Persian Languages

An Analysis of the Errors in the Auto-Generated Captions of University Commencement Speeches on YouTube

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