In early March, the U.S. Department of Defense announced that it awarded a $10 billion language services contract, splitting the budget among nine firms. The contract\u2019s whopping value is a reminder of how important\u2014and often how difficult\u2014accurate translation is. This holds true in the private sector every bit as much as it does for public entities.\r\n\r\nFor organizations maintaining content-rich and frequently evolving websites, keeping text up-to-date in various supported languages can be a challenge. Three automation approaches often are used to expedite the process.\r\n\r\n \r\n<h3>Simple Machine-Based Translation<\/h3>\r\n \r\n\r\nWith this approach, translations are performed by software. The software analyzes the text, detects the language, and produces the translated version in the requested target language.\r\n\r\n\u201cThis is the fastest of the options\u2014for example, some solutions respond to requests in a matter of seconds,\u201d Anupam Dutta, WebINTENSIVE project manager, points out. \u201cAnd it can be the cheapest\u2014some services presently charge a few dollars per million characters.\u201d\r\n\r\nThe downside: it is by far the least trustworthy option since it primarily just provides a direct word-to-word translation without context or nuance. \u201cAnd synonyms can present a challenge,\u201d Dutta points out.\r\n\r\n \r\n<h3>Neural Machine-Based Translations<\/h3>\r\n \r\n\r\nThis method also relies on translation by software, but increases translation accuracy compared with simple machine-based translation because the system learns words, phrases, and rules and uses its understanding of these to facilitate translations.\r\n\r\n\u201cNeural machine translation can provide better results through evaluating full sentences, and learning from and selecting words based on context,\u201d says Justin Cameron, WebINTENSIVE manager.\r\n\r\nFor example, the new Google neural machine translation system is more accurate than its old system. It is 58 percent more accurate at translating English into Chinese, and 87 percent more accurate at translating English into Spanish.\r\n\r\n\u201cHowever, accuracy and nuance of neural-enhanced translation still lags behind the capabilities of a professional, native-language human translator,\u201d Cameron notes.\r\n\r\nPrices today can range from $40 to $65 per million characters.\r\n\r\n \r\n<h3><strong>Machine Translations Vetted by Professional Translators<\/strong><\/h3>\r\n \r\n\r\n\u201cThis approach produces the translations with the highest accuracy, as human native speakers review text and correct machine errors, though, of course, it is the slowest of the three processes,\u201d says Dutta. For example, a 500-word webpage may take anywhere from one to three days to translate, depending in part on the complexity of the language pair.\r\n\r\n\u201cEnglish to Spanish, which are relatively similar tongues, takes less time to translate than Korean to Urdu,\u201d Cameron explains.\r\n\r\nThis also is the highest-budget option, averaging today between 10 cents to 20 cents for each word of a language pair. At times, discounts can be negotiated.\r\n\r\n \r\n<h3>Have Questions?<\/h3>\r\n \r\n\r\nTo learn which of these approaches may be best for your website, just call: 212-447-1100.