Discussion Week 10

Discussion week 10

fanny Ndouagni

[Name of the Institution]

Discussion week 10

Introduction

Machine translation (MT) is based on automatic software that can perform the tasks of translation content into target langauges. The software can be performed by humans or it can work by itself to convert speech into different language. MT systems can translate million words that is not possible to perform by traditional manner. Companies such as Google, Bing has buyied the generic MT and connected to their systems which provide translations to their customers worldwide.

Response 1

Machines trnaslators are adopted in various organizations performing different functions, however, it still lacks in the telecommunication companies. Even some of the largest telecommunications firms has not utilized the technology yet such as ‘Verizon wireless’. It is a largest wireless broadband in the US covering almost 98 percent of the population. The company has latest technologies interms of access and products, however, it still lack the machine translation. Although, the wireless device is more usefull for native speaking people. It is still hard for French, Swedish or any other language speaking people to convey their messagesCITATION Exp13 \l 1033 (Mikolov, Sutskever, & Quoc, 2013).

Machine translation is a new technology but it can be proved extremely beneficial for people around the world, where they will be able to speak in their native languagea. The machine will translate their words instead of selecting option of English, and making struggle to convey their messages in US language.

Response 2

Machine translation is still not acceptable in many companies. They believe that machines cannot perform the tasks accurately. Many companies are still of view that humans can do better than machines. However, in the developing global market which is transforming into artificial technology, it is important that translations machines should be regularly updated CITATION Bur11 \l 1033 (Burch & Koehn, 2011).

Machine translations should be made capable to serve vast majority of cultural groups. The quality output of machines is based on its training, so it is necessary to train them in your desired domain. It will help the software work efficiently in different languages.

References

BIBLIOGRAPHY Burch, C. C., & Koehn, P. (2011). Findings of the 2011 Workshop on Statistical Machine TranslationWMT '11, Proceedings of the Sixth Workshop on Statistical Machine Translation. the Association for Computing Machinery, (pp. 22-64). Edinburg, Scotland.

Mikolov, T., Sutskever, L., & Quoc, V. (2013). Exploiting Similarities among Languages for Machine Translation. Cornell University.