MACHINE TRANSLATION

Machine translation is the translation of text by a computer, with no human involvement.

Machine translation, sometimes referred to by the abbreviation MT (not to be confused with computer-aided translation, machine-aided human translation (MAHT) or interactive translation) is a sub-field ofcomputational linguistics that investigates the use of software to translate text or speech from one language to another. On a basic level, MT performs simple substitution of words in one language for words in another, but that alone usually cannot produce a good translation of a text because recognition of whole phrases and their closest counterparts in the target language is needed. Solving this problem with corpus and statistical techniques is a rapidly growing field that is leading to better translations, handling differences in linguistic typology, translation of idioms, and the isolation of anomalies.

Pioneered in the 1950s, machine translation can also be referred to as automated translation, automatic or instant translation. There are two types of machine translation system: rules-based and statistical: Rules-based systems use a combination of language and grammar rules plus dictionaries for common words. Specialist dictionaries are created to focus on certain industries or disciplines. Rules-based systems typically deliver consistent translations with accurate terminology when trained with specialist dictionaries. Statistical systems have no knowledge of language rules. Instead they "learn" to translate by analysing large amounts of data for each language pair. They can be trained for specific industries or disciplines using additional data relevant to the sector needed. Typically statistical systems deliver more fluent-sounding but less consistent translations.

In the past when we had to figure out the meaning of a word from another language, we made use of a dictionary. Not only was this a very time consuming task but it was kind of irritating owing to the fact that it was difficult to interpret the meanings. Moreover, when an entire paragraph or note had to be translated, this could be very difficult because one word had several meanings. So what to do? That's where the machine translator came into the picture.

But what exactly is a machine translator? Since the advent of the 21st century, there have been a lot of developments and new technologies have been introduced which have made life more convenient and simple. A machine translator is such a small yet useful device. Machine translation, which is also known as Computer Aided Translation, is basically the use of software programs which have been specifically designed to translate both verbal and written texts from one language to another. In the face of rapid globalization, such services have become invaluable for people and you just cannot think of any disadvantages of machine translation.
Current machine translation software often allows for customization by domain or profession (such as weather reports), improving output by limiting the scope of allowable substitutions. This technique is particularly effective in domains where formal or formulaic language is used. It follows that machine translation of government and legal documents more readily produces usable output than conversation or less standardised text. Improved output quality can also be achieved by human intervention: for example, some systems are able to translate more accurately if the user has unambiguously identified which words in the text are proper names. With the assistance of these techniques, MT has proven useful as a tool to assist human translators and, in a very limited number of cases, can even produce output that can be used as is (e.g., weather reports). The progress and potential of machine translation have been debated much through its history. Since the 1950s, a number of scholars have questioned the possibility of achieving fully automatic machine translation of high quality.[2] Some critics claim that there are in-principle obstacles to automatizing the translation process.[3]

Nevertheless, like everything has its pros and cons, so does machine translation.

Firstly let's go over the advantages of machine translation: When time is a crucial factor, machine translation can save the day. You don't have to spend hours poring over dictionaries to translate the words. Instead, the software can translate the content quickly and provide a quality output to the user in no time at all. The next benefit of machine translation is that it is comparatively cheap. Initially, it might look like a unnecessary investment but in the long run it is a very small cost considering the return it provides. This is because if you use the expertise of a professional translator, he will charge you on a per page basis which is going to be extremely costly while this will be cheap. Confidentiality is another matter which makes machine translation favorable. Giving sensitive data to a translator might be risky while with machine translation your information is protected. A machine translator usually translates text which is in any language so there is no such major concern while a professional translator specializes in one particular field. Then the disadvantages of Machine Translation: Accuracy is not offered by the machine translation on a consistent basis. You can get the gist of the draft or documents but machine translation only does word to word translation without comprehending the information which might have to be corrected manually later on. Systematic and formal rules are followed by machine translation so it cannot concentrate on a context and solve ambiguity and neither makes use of experience or mental outlook like a human translator can. These are the primary advantages and disadvantages of using machine translation for a document regardless of language. They can be weighed and the right decision can be made depending on the information and the quality that is required. We don't use machine translation for any of our translation projects - from your language to Simplified Chinese, Traditional Chinese, Mandarin & Cantonese.

The machine translation is a field of computer science that focuses on converting written text or verbal speech from one natural human language to another. Research in this field began in the 1950s and has since advanced to the point that, as of 2011, several machine translation systems were available for public use. Completely accurate translation is very difficult to attain using machines, however, and many challenges in this field had yet to be solved. The general technique used in machine translation is to convert words from one language into their equivalents in another tongue, using a computerized dictionary. Human languages are complex, however, and phrases can often have multiple meanings, so effective translation programs must take entire sentences into account. These programs must compute the meaning of each word. For instance, the word "book" can be a noun as in "he read a book" or a verb such as "he will book a flight." By analyzing context, programs can determine the best words for the translation. Machine translation algorithms must also consider the grammar structure of the target language. As an example, for the English words "red shirt," the direct translation into Spanish is "roja camisa." Correct Spanish grammar places adjectives after nouns, however, so proper translation must follow this grammar rule and rearrange the Spanish result as "camisa roja." Grammar rules might be simple to apply when only two words are involved but can become complex and difficult for machine translation to process when entire sentences and paragraphs must be converted. Despite advances in machine translation, computer programs in the early 21st century still were prone to mistakes. A technique to solve this problem is machine-aided human translation, in which professional human translators use the program. These professionals are aware of the limitations of machine translation, so they are able to find and correct common mistakes. Combining human and machine translation services allows large amounts of text to be converted both quickly and accurately.

WHAT ARE THE MAIN TYPES OF MACHINE TRANSLATION?

Rule-Based Machine Translation systems use large collections of rules, manually developed over time by human experts mapping structures from the source language to the target language. The human factor in rule-based systems helps deliver fairly good automated translations with predictable results. However, due to significant manual labor, rule-based systems can be quite costly, time consuming to implement and maintain and – as rules are added and updated – these systems have the potential of generating ambiguity and translation degradation over time. Statistical Machine Translation systems use computer algorithms to produce a translation that looks best statistically from millions of permutations. Statistical models consist of words and phrases learned automatically from bilingual parallel sentences, creating a bilingual “database” of translations. The attractiveness of statistical systems comes from the level of automation in building new systems using its machine learning capabilities, leading to rapid turnaround time and the low cost of processing power required for constructing and operating these statistical models. However, the major downside with this type of engine is the “data-dilution effect” caused by scarcity of suitable data for ‘training’ these data-driven systems. Hybrid Machine Translation. In order to address quality and time-to-market limitations, many Rule-Based Machine Translation developers are augmenting their core technology with Statistical Machine Translation technology to create ‘Hybrid Machine Translation’ solutions. Hybrids provide some quality improvement benefits, however, they keep the costs of Rule-Based systems high by adding complexities of managing side-by-side systems. Next Generation Approaches. New “augmented” Machine Translation solutions are emerging, upgrading the capabilities (and overcoming the limitations) of Statistical Machine Translation. By introducing sophisticated data pre-processing (Language Transformation), Language Optimization Technologies and terminology management solutions, these new Statistical MT solutions are achieving the same quality improvements introduced by Hybrid MT while dispensing with the need for legacy technology – delivering a new standard in multi-lingual communication solutions.

What is the human translation:

The human translation process may be described as: Decoding the meaning of the source text; and encoding this meaning in the target language. Behind this ostensibly simple procedure lies a complex cognitive operation. To decode the meaning of the source text in its entirety, the translator must interpret and analyse all the features of the text, a process that requires in-depth knowledge of the grammar, semantics, syntax, idioms, etc., of the source language, as well as the culture of its speakers. The translator needs the same in-depth knowledge to re-encode the meaning in the target language. Therein lies the challenge in machine translation: how to program a computer that will "understand" a text as a person does, and that will "create" a new text in the target language that "sounds" as if it has been written by a person. In its most general application, this is beyond current technology. Though it works much faster, no automated translation program or procedure, with no human participation, can produce output even close to the quality a human translator can produce. What it can do, however, is provide a general, though imperfect, approximation of the original text, getting the "gist" of it (a process called "gisting"). This is sufficient for many purposes, including making best use of the finite and expensive time of a human translator, reserved for those cases in which total accuracy is indispensable. This problem may be approached in a number of ways, through the evolution of which accuracy has improved.

We employ ONLY human translators for any and all of your Chinese translation projects!