In 2017, CSA Research conducted the first large-scale, pro-bono, survey-based research on gender issues in language services. With over 2,000 respondents, the findings provided objective and reliable information about how women and men involved in the industry perceive these issues. On the eve of the #metoo movement, the report kicked off industry-wide discussion on the role gender plays. It provided detailed – and surprising – results for North America and Europe.
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Need help with building effective business cases and presentations that lead to increased investment to drive global growth? CSA Research recently analyzed data from 20 global companies to determine what works and what does not when making the case in front of executives. Here are six actions you can take to improve the likelihood that your next investment proposal will be accepted.
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It’s rare to go for more than 24 hours without receiving an e-mail that references “digital transformation” in some way. Organizations of all types – commercial, government, NGOs, non-profits, and educational institutions – spend a lot of time discussing the challenges and changes required by digitalization. But who’s taking responsibility for the global ramifications of these initiatives? How are companies measuring success or failure? How will global content evolve as a result? CSA Rese...
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In recent months, we have increasingly heard from enterprise localization groups that their executives are pushing for the adoption of neural machine translation (NMT), driven largely by a very successful public relations campaign from Google that has touted the very real improvements in NMT over the past two years. Unfortunately, some business leaders have seen media coverage and concluded that they no longer need language professionals and can simply replace translators with the “magic” of AI.
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User-generated content (UGC) has garnered a lot of attention due to the challenges it poses for localization, such as an abundance of spelling errors, the extent to which its meaning depends on context, a lack of consistency, and time sensitivity. But even as enterprises and language service providers (LSPs) struggle to deal with it, another type of generated content has been quietly swelling into a looming tsunami: machine-generated content (MGC). Today, increasing quantities of content appear ...
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It’s almost impossible to open one’s email or social media feed without skimming one or more messages entreating the reader to “follow the path to digital transformation” or to “recognize how artificial intelligence (AI) is changing digital transformation.” But how much attention should LSPs pay to what’s going on in this area? CSA Research recently launched an initiative to find out. In the meantime, here’s what our preliminary results show.
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I have an interest in 19th-century sporting newspapers and would like to have them in digital form. Unfortunately, these newspapers used almost microscopic fonts, the type was often heavily worn, and their paper has degraded over time. Despite these problems, humans usually don’t have any trouble reading them, but optical character recognition (OCR) is another matter.
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Moving content from one support knowledge base (KB) to another is hard enough in one language, let alone in two or more. In our recent interviews with 36 global firms about how they create and manage multilingual support content, KB migration elicited the most spirited discussions. Here are five pieces of advice from our research to improve the chances that your next migration initiative will go as smoothly as possible in one language or many.
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Translation technology has reached an inflection point, swept up in the big trends affecting every industry: big data, cloud computing, and artificial intelligence (AI). Language platforms are being renovated or replaced as enterprise buyers and innovative language service providers seek to align their language systems with the rest of their technology stacks. Dated monolithic translation management systems (TMSes) are giving way to microservice- and cloud-based architectures, with machine learn...
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Chatbots are rapidly becoming ubiquitous in marketing and support. The potential for brands to interact with customers using natural language – and perhaps a bit of personality – without needing an army of paid human agents is driving major investment from enterprises. Tech giants – from Google to Facebook and IBM and Weibo to Microsoft – have started a virtual race to dominate this field. However, what is missing in this picture so far is serious attention to multilingual needs. Amazon, App...
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