عنوان مقاله:

نویسندگان:

Marziyeh Khalilizadeh Ganjalikhani

This paper aims to propose crowdsourcing translation as an effective solution as well as being time saving and economic in improving the translation quality of the MTs. In the present paper the performance of two MTs, Google Translate and Microsoft websites, regarding the translation of Homonyms into Persian Language over time has compared and contrasted. The researcher had compared these two MTs’ performance in translation of Homonyms 3 years ago and has used the same data in both Machines to see their performance after 3 years. The results show that Google Translate website performance regardging the accuracy of translation which is a pivotal issue in Machine Translation has been improved significantly comparing the Microsoft website but yet it needs a great deal of correction and post editing regarding the translation of Homonyms at least. Since Google translate is an example-based translation Machine, therefore the enrichment of vocabulary repertoire excels its performance in every aspect. One of the methods used for achieveing this enrichment is through the user’s cooperation. It can be concluded that the more users cooperate in the translation the better the performance becomes. Since crowdsourcing translation is a process by means of which organizations can tap into the wisdom of their dedicated external community and use the wisdom for their benefit, the paper is closed with proposing Crowdsourcing Translation which is a collective and human-based translation as a very effective tool to raise the quality of Translation significantly in exampled-based MTs in a short amount time.

Crowdsourcing Translation, Homonym, Machine Translation,

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Khalilizadeh Ganjalikhani، Marziyeh، 1398، Crowdsourcing Translation: A Tool to Raise The Translation Quality of MTs، اولين کنفرانس بين المللي مطالعات زبان انگليسي، https://conf.ui.ac.ir/fa/archive_index.php?c=icels&aid=1506051