Val Swisher is the founder and CEO of Content Rules, a professional services firm specializing in content strategy, creation, and quality. The presentation discusses how machine translation is becoming more widely used but relies on high quality source content. Poor or ambiguous content can train machine translation engines incorrectly, resulting in poor translations that require extensive post-editing. Pre-editing source content to make it more consistent, grammatically correct, and globally ready saves time and money compared to post-editing translations by reducing issues and improving quality.
According to the CMO Council and Netline in their June 2013 survey, “Understanding How BtoB Buyers Source, Value, and Share Content Online,” 87% of respondents stated that content had a moderate to major impact on their buying decisions.For far too long, content has been treated as something that simply describes, positions, or touts a product. Technical content, in particular, has long been an after thought, something not deemed important. If we don't treat content as a strategic asset, it is just garbage. And if we put garbage into machine translation, it is just exponentiated garbage.
One poorly written source document = many poorly translated resulting documentsPoor source content = more post editing Problems exponentiate based on number of language pairs