Tag: MT Post-editing

Machine Translation and Compliance

Machine Translation and Compliance

 

Compliance management is no simple task in today’s world. The sheer volume of data involved is intimidating enough. But when that data is in multiple languages, you have an additional layer of complexity to manage as well as another significant expense to budget for.

Machine translation is no replacement for expert human translators. But it can help solve some of the compliance problems multicultural organizations face.

Internal Compliance Monitoring

Ideally, organizations should aspire to catch (and end) compliance issues as early as possible. Firing employees is an expense in and of itself, and if you address these issues quickly you can often solve the problem with education rather than termination. Meanwhile, whether the behavior in question is illegal, unethical or just plain risky, the sooner you put a stop to it, the less likely you are to get stuck with expensive fines.

Is your organization monitoring employee communication to identify concerning behavior? Machine translation makes it possible to understand, analyze, and review large amounts of archived data in foreign languages, so you can stop problems before they start.

eDiscovery Compliance

Businesses today generate vast amounts of electronic documents and communications. That makes eDiscovery like looking for needles in a haystack, sifting through tons of irrelevant information to find materials that are relevant to the case. And of course, there are penalties for not identifying and producing all of the necessary documents in a timely manner.

The most workable solution is appropriately-deployed machine translation followed by review and post editing from human experts, when required. Machine translation is not a substitute for human translators. That said, in large cross-border cases, machine translation can be used to produce documents for opposing counsel, and then human translators can translate only those documents that seem relevant. Machine translation can also help your team identify and classify large numbers of documents for review.

Data security

Using machine translation when applicable can also improve data security, as long the platform used is secure. (Note: That means free platforms are strictly off limits!) No matter how careful your employees are, each person who accesses a document creates a new security risk. Machine translation can reduce the number of people who need that access to reduce security vulnerabilities.

Machine Translation and Compliance Budgets

As the cost of compliance goes up, so does the pressure for businesses to make their compliance procedures more efficient. Machine translation can help optimize your compliance budget by only using human translators when necessary.

When Machine Translation is a Compliance Nightmare

When wielded wisely, machine translation can be a powerful weapon in your compliance arsenal. But it can also be risky. For instance, if individuals in your organization rely on free online translation services, your data security could be at risk.

Last year, employees at Norway’s Statoil discovered that sensitive data translated using Translate.com’s free MT tool was available to the public via a simple Google search.

Though the quality of machine translation has improved by leaps and bounds during the past few years, it’s still not a substitute for human translators when clear and accurate translations are required. If inaccuracies make your translations misleading or incomprehensible, that’s a compliance risk, too.

 

Reference: https://goo.gl/krFhns

‘Human Parity Achieved’ in MT

‘Human Parity Achieved’ in MT

According to Microsoft’s March 14, 2018 research paper with the full title of “Achieving Human Parity on Automatic Chinese to English News Translation,” a few variations of a new NMT system they developed have achieved “human parity,” i.e. they were considered equal in quality to human translations (the paper defines human quality as “professional human translations on the WMT 2017 Chinese to English news task”).

Microsoft came up with a new human evaluation system to come to this convenient conclusion, but first they had to make sure “human parity” was less nebulous and more well-defined.

Microsoft’s definition for human parity in their research is thus: “If a bilingual human judges the quality of a candidate translation produced by a human to be equivalent to one produced by a machine, then the machine has achieved human parity.”

In mathematical, testable terms, human parity is achieved “if there is no statistically significant difference between human quality scores for a test set of candidate translations from a machine translation system and the scores for the corresponding human translations.”

Microsoft made everything about this new research open source, citing external validation and future research as the reason.

Reference: https://goo.gl/3iFXXG

Machine Translation Post-Editing Types

Machine Translation Post-Editing Types

Post Editing is the next step after completing the machine translation (MT) process and evaluating its output. A human translator processes the document to verify that the source and target texts convey the same information and that the tone of the translation is consistent with the original document. The quality of machine translation varies and affects the subsequent effort required for post editing. There are contributory factors to the quality of the MT such as the clarity and quality of the source text; it is important to make sure that the source text is well-written and well-suited for machine translation beforehand. Other considerable factors that affect MT output quality include: the type of MT used, and the compatibility of the source and target languages.

There are two types or levels of post editing

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Evaluation of Machine Translation Output

Evaluation of Machine Translation Output

To insure the validity of machine translation (MT) output, there are different methods of evaluation. A rudimentary form of evaluation is to perform a “round-trip translation”, meaning that the original text is machine translated into the target language, and then the result of that process is translated back into the original language to test the quality of the machine translation. As the quality of machine translation continues to improve, a reliable method for evaluation will also be necessary. Currently, there are two main types of evaluation used for machine translation: human and automated.

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Machine Translation History & Approaches

Machine Translation History & Approaches

Machine Translation (MT) refers to automated language translation. The concept has been around since the 1600’s but has come into its own beginning in the twentieth century. Along with the invention of electronic calculators came the development of ways to adapt computer technology to language translation of documents. Research became prevalent at universities in the mid 1950’s to develop and test machines to perform tasks previously only possible by human translators.

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