The Development Of Machine Translation
Human societies need to interact with each other, and this interaction can be instrumental in enhancing human culture and knowledge. Communication between societies encompasses a wide range of topics, including economic, political, cultural, scientific, and so on, all of which are interdependent and the role of translation in communication between communities cannot be ignored.
With the significant advances in computer science and its application in various fields, including linguistics as well as the opening up of a new space in the field of linguistics, including cognitive linguistics and applied linguistics, the idea of machine translation has become more pronounced. Expanding international relations in many areas such as science, politics, economics, culture, and the vibrant position of language in global interactions, which manifests itself in the form of political, religious and cultural discourses; Makes it more visually appealing. But besides the above, in an age where the speed of transferring scientific, media, and so on data is highest, speed in translation is inevitable. Hence, machine translation continues to present itself as a challenge in the field of global communications. Machine translation, regardless of its different types, has many problems that are controversial among translation theorists.
Work on the translation machine coincided with the invention of the computer in the 1940s. The primary translation machines were designed to use a bilingual name for the translation of various texts. The translation was limited to lexical translation and was not a translation of the syntactic structure of the source language or the intent. These were called direct translation methods. However, in the 1980s, several translation systems were introduced to the market, using indirect methods of translation. The reason for using the indirect word is simply because such machines do not translate the text directly from the source language to the target language, but instead translate the source language into a ‘interlingua’ and then into the target language.
Google Translator Toolkit is one of the newest on-line translation features. This toolbox is actually a tool for editing translation texts that allows users to easily edit translations made by Google translators. Google Translator Toolkit has features that can make it a useful tool for translators and even professional translators. One of the features of this toolbox is that it allows users to access Google Translation and other users simultaneously. In addition, users can share their translation online with the help of this tool. On the other hand, the toolkit is very simple to work with and the interface is designed so that users can easily enjoy its many features.
Technology expands human capacity. More general technologies are a set of tools. Some of them affect our communication and consequently translation. Technology and collaboration in the language industry and therefore in the professional life of the translator are essential. Technologies such as computer-aided translation (CAT), machine translation (MT), terminology management systems, alignment tools, and various forms of language technology have been incorporated into the translation profession.
Machine translation (MT) works by referring source text to groups with a large amount of source language paired with its translation into the target language. The likelihood of achieving high quality MT has been questioned or criticized. Therefore, a common method in MT is to use it for the production of crude or rough drafts such that pre-editing or post-editing human targeted editing is required to improve translation quality. However, with the advances in artificial intelligence, there has been a renewed interest in the use of MT in a variety of areas including language learning, health education and commerce.
Google Translate is perhaps the most widely used online translation service, and since 2016, over 500 million people have translated 100 billion words daily in 103 languages. Google Translate (GT) was introduced in 2006, and the service was updated in 2016 with a Nervous Machine Translation (NMT) model. With the change, CEO Google Sander Pichai stated that its machine translation has improved from a score of 3. 694 (out of 6) to 4. 263 and is close to the human level quality of 4. 636.
Google Translate is perhaps the most widely used online translation service, and since 2016, over 500 million people have translated 100 billion words daily in 103 languages. Google Translate (GT) was introduced in 2006 using a Statement-Based Machine Translation (PBMT) model, and the service was updated in 2016 with a Nervous Machine Translation (NMT) model. With the change, CEO Google Sander Pichai stated that its machine translation has improved from a score of 3. 694 (out of 6) to 4. 263 and is close to the human level quality of 4. 636.
Today, there is a great deal of pressure to publish scientific texts in English. Translation of scientific texts plays a central role in all academic fields. Thus, in recent years, a growing body of literature has begun the function of translating academic texts from different perspectives, including the history of science and translation, ethics. And ideology, translator training, and the popularity of knowledge.
Translation of academic discourse involves complex topics that arise at different levels. These range from the general approach or translation strategy used by the translator to topics related to a particular text or even its effective linguistic or contextual features. In discussing its translation for specific purposes with a focus on the economic literature, Stolze (2003) points out that “with respect to the intrinsic relationship between the text as a whole and its constitutional elements, the holistic view is being complemented by an analysis of the predicative mode, which shows in the particular style of the text characterizing its author. ”
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