Translating data for machine learning purposes requires more than just native speakers. Our linguists are trained in data collection translation projects to adapt their translation style to the task and to follow the ML rules as specified. This provides a consistent quality data set.
We make your data more usable for Natural Language Processing (NLP) training models by translating it.
It is crucial to have clean data sets when teaching AI to interpret written and spoken language. DK provides multilingual sets of data consisting of text, voice, and image data that are perfect for test and training sets. DK has a large number of qualified resources. We can expand to include 1000+ linguists for high-quality data set translation within 2 to 4 weeks.
In order to have high-quality AI, you need to have good, clean data sets. We collect data based on your system’s specific requirements. We have qualified resources located all around the world, so we can quickly scale up or down according to your project’s needs. We also cover more than 60 languages. Our process involves humans and machines working together.
DK offers a customized MT engine that gets smarter over time as it learns your preferences. We’ll work with you to determine the best solution for your content, from baseline engine selection to workflow setup. We have a detailed quality assurance process that optimizes time and cost savings while maintaining the right level of quality.
Quality Assessment of Machine Translation
Trained linguists review your machine-translated context to ensure it meets quality standards.
Machine translation can work for certain types of content. Yet, in many cases, quality lags behind human standards. Our quality assessment team helps you take advantage of lower costs without sacrificing quality. DK has qualified linguists in over 60 languages to evaluate your machine translation.