It has taken social and mobile – plus the empowerment of consumers to influence the message – for content to finally grab the undistracted attention of executives. But they’re not only wrestling with content in its simplest forms controlled by employees. They must also take into account material created “in the wild” – outside of their organizations – where it morphs into assorted flavors through local languages, dialects, and cultures.
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Two years ago, CSA Research determined that the language sector faced a perfect storm as industry players incrementally improved efficiency, innovated services and processes built on newer technology and streamlined practices, and confronted disruptive intrinsic and external changes that were transforming the market.
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Today CSA Research released the first in a series of reports that examine gender and family issues in the language industry. Based on our survey of 2,195 professionals who work with language services, this free report provides insights into the role gender and family plays in the field. We developed this pro bono research with the support of GALA and Women and Localization in order to understand how language workers compare to other industries. The report shines light on topics ranging from pay ...
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For several years, the field of quality checking tools has been largely stagnant, with incremental updates to established tools. Recently, TAUS’ Dynamic Quality Framework (DQF) and the EU’s Multidimensional Quality Metrics (MQM) have set the stage for new developments in quality assessment methods thanks to their new methods and push for standardization. In this blog, we’ll review three new market entrants that are hoping to shake up this area.
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CSOFT (#22 on our global list of the 100 largest LSPs) has banked on mobile being a driving force behind language needs. In December 2015, the company released Stepes (pronounced /'steps/), a human-powered mobile translation app designed to mobilize professional translators and Uberize the world’s bilingual population in the process. Last year, the company broadened the offering to support on-demand social media and image translation, again harnessing the power of the crowd. However, 2017 w...
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How many times have you heard that "localization is special" or "globalization only affects a few departments?" Probably more than you can count. Why are these attitudes still held by otherwise informed middle managers and executives? Because localization or globalization doesn't register as a business process for them.
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Last week Luxembourg-based AMPLEXOR (#9 on CSA Research's 2016 list of largest LSPs) acquired U.S.-based Sajan (#30) for US$28.5 million. This amounts to US$5.83 per share for publicly-traded Sajan, a 46% premium over the current share price. Because Sajan will go private, it has substantial disclosure and shareholder protection requirements under the U.S. Security and Exchange Commission's Rule 13e-3 Rule. That regulation also limits what it or AMPLEXOR can say now about the deal beyond...
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Turning something that's perceived as cheap or ugly into a more valuable or beautiful object has been the goal of alchemists through the centuries. Many languages have expressions that echo their quest to turn lead into gold. An English proverb maintains that you can't make a silk purse out of a sow's ear. The French take a different animal to task, "On ne saurait faire d'une buse un épervier" – you can't turn a buzzard into a sparrow hawk. And a Russian might say ...
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Imagine yourself in a café in Paris or on a beach in Cancún, running into some gorgeous human specimen you just can’t help but approach. You walk up to the person, offer them a hearing device, and point for them to put it in their ear while you pop one in yourself. Then you launch an app on your smartphone and start communicating via the help of machine interpreting, hoping the app will accurately translate your best pick-up line.
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Every new development in the field of machine translation (MT) is accompanied by a set of numbers that purport to show dramatic improvement in terms of quality, usually BLEU or METEOR scores. These measures use a scale from 0 to 100 to quantify how similar the MT output is to one or more human translations of the same source text based on a mechanical analysis of how many of the same words show up and how likely they are to appear in the same order.
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