Translation Software in Enterprise

In an ideal world, everyone would speak the same language or at least be able to understand other languages fluently. But we don’t live in that ideal world, yet. We do, however, live, work, and interact in a global society, where effective communication with co-workers is vital, and machine translation software has become a must for any company that works on internationally.

There are many types of machine-based translation software. The two types most talked about assist translators and those who can do the translation themselves.

Don DePalma of Common Sense Advisory, Inc., a market research company that works with international clients, gave his understanding of the different types. “The first, assisting human translators in doing their work, are called CAT (computer-assisted translation) tools. They allow the translator to view translations of the same text that had already been translated by him, her, or someone else,” DePalma explained.

“The other major type is what we call machine translation software or MT for short,” he said.” MT is a software application that takes text in a given language and translates it into another. In its most direct form, it only requires a human to input the text as you have probably done at Google Translate or Microsoft Bing Translate.”

There are two main ways MT software can be used to facilitate communication, Hassan Sawaf, chief scientist with SAIC Linguistics, added. The first is by enabling communication on a level at which it does not make logistical or financial sense to involve a human translator in the process- internal email, for example. The second is to have a human translator post-edit text already translated by MT software. This process increases human translator efficiency by about 400 percent.

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“Most MT software only translates text communication; however some MT software is integrated with automatic speech recognition (ASR) technology,” Sawaf said. “ASR converts voice input into text with many advanced systems then interpreting and acting on its meaning. Apple’s Siri is an example of ASR technology that many would recognize. MT software with integrated ASR technology not only translates text, but produces speech-to-speech and speech-to-text translations as well.”

Both DePalma and Sawaf pointed out that translation software works extremely well in the cloud. In fact, the cloud is a key enabler of translation software.

“The cloud also enables translation technology to be mobile,” said Sawaf. “While some MT software can be localized to a tablet or smartphone, most require access to the processing power found in the cloud. Connecting to the cloud also helps MT software learn from the users’ experiences and improve over time. However, some use cases will require the MT technology to be localized, to save roaming costs, or if the user has to use translation technology in areas that have no or very limited internet and cell network coverage.”

When deciding whether or not to use machine translation, consider the value of your content. If it’s highly valuable, mission-critical content, such as marketing messaging, MT will not accomplish your objectives. However, if it’s something of lower value like user support material or internal-facing content, MT with human post-editing may be the solution for you.

Alyssa Paris, marketing manager with Acclaro, a global translating business, offered the following tips for successfully using machine translation:

1. Make sure your source text is cleanly written and correct, free of idiomatic phrasings and generally machine translation-friendly. It’s also best if there’s a uniform tone throughout.

2.  Your language vendor should establish upfront a dictionary of key terms. They should then have it reviewed and confirmed by all language stakeholders at your company.

3.  Determine which approach — rules-based, statistical or hybrid — is best for your project. Statistical engines are appropriate if you have huge volumes of existing bilingual content. Otherwise, consider rules-based or a hybrid solution.

4.  Invest in human post-editing for improved accuracy and quality. However, the editors should only change what is lexically essential to ensure understanding.

5.  Have realistic expectations for the quality of the content you’re going to achieve via machine translation. Your content won’t be beautiful but if you follow these best practices, it will be comprehensible and effective.

With the integration of ASR and MT, translation technology is at a really exciting time right now, Sawaf said. With the increased globalization and mobility of business, the smart use of translation technology can be a real competitive advantage for companies.

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