IELTSFever FREE Online Test Day 71(08-03-2021)

IELTSFever FREE Online Test Day 71

Must Read These Instructions before participating in Exam

The answer to each and every question is mandatory otherwise we will not accept it. Send your answers to [email protected] with your name, city along with the question( in the subject field of email), and must send us the answer within 24 hours of the question.  We will not respond to late answers and without a name, question no answer will be considered.

Academic Writing Task 1

The graphs show the number of deaths caused by six diseases


General  Writing Task

After being involved in an accident, you were looked after by another person. Write a special letter to express your thanks.

Yo, u should write at least 150 words.
You should spend about 20 minutes on this task.

General/ Academic Writing Task 2

Machine translation (MT) is slower and less accurate than human translation and there is no immediate or predictable likelihood of machines taking over this role from humans.

Do you agree or disagree? Write at least 250 words.

Academic /General speaking

Describe a person who you think is especially helpful

You should say:

  • who he/she was
  • how you met him/her
  • what he/she did to help you

and say what you learned from the experience.


IELTSFever FREE Online Test Day 71(08-02-2021)

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1 thought on “IELTSFever FREE Online Test Day 71(08-03-2021)”

  1. Mustufa Kamaal Afghan

    A common opinion is that Machine translation (MT) is not perfect and as fast as a human translator. Due to this, the translation realated jobs can not be handed over to the machines completely, owing to this the chances of mass adoption seem bleak in the near future. I agree with this view because I believe that machine will learn as much as we feed to them.

    One the one hand, it is evident that machines are doing incredible job to assist us with routine tasks consequently saving humungous time and efforts. My recent experience with an online translation service was satisfactory. Translation to a foreign language was almost accurate as vetted by a native speaker. Similarly, the script result on dictation software has been also useful. Overall, it is worth pursuing although may sound challenging to cope up with ever growing terminologies, phrases, words, and localization for a machine to understand and learn by itself. On top of it, a machine may not understand context or background of the subject and may lead to faulty output. This may happen to a human as well.

    On the other hand, a machine’s knowledge is limited to what is being fed, and hence dependency on input content. At a globla level, thousands of languages and dilects are spoken. And there are hundreds of various scripts used for writing. One can not imagine a machine to learn those and act as human translator. However a reasonable output is expected from the machines so that it can be used as input in the next step of a process.
    If a machine is limited, it is us who has set the limitation. It requires high degree of actual interaction with human being to learn and udpate the knowledge for translation. If the horizen is broadened, and machines are exposed to more realistic learning scenarious, one can expect better and quicker results.

    In conclusion, it is proven that Machine translation (MT) is not as accurate and in the near future it is less likely to be completely entrusted to the machines. And in my opinion, there should be specific initiative taken to increase machine learning for granular visibility resulting into true and faster translation.

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