KantanQES - More effective communications with A.I.
KantanQES empowers global organizations to understand the quality of machine translation, and to use machine translation in a more intelligent way.
Predictive Quality Estimation
KantanQES uses cognitive computing and deep learning to recommend high-quality machine translation texts. This can be used to prioritize translation effort, reduce costs and accelerate the delivery of multilingual content. This helps international organizations increase their competitiveness in the global market by providing customized multilingual content rapidly. KantanQES uses neural modelling to determine the quality of machine translation output which can be helpful in determining resource requirements, translation budgets and project timelines.
Improve communication effectiveness
By combining artificial intelligence and neural machine translation, KantanQES provides an objective confidence score or quality estimation for each source sentence.
How KantanQES Works
Prioritize translation activities
KantanQES (Quality Estimation Score) uses advanced neural network modelling to predict the translation quality of every sentence. These predictive scores can be used to plan project schedules, determine project costs and assign suitable resources in order to deliver projects on-time and within budget.
Ready to learn more?
KantanAI works with some of the world’s largest organization to improve their products and services and deliver smoother customer journeys with A.I.
KantanQES creates a detailed project management report of all segments within a KantanMT project. This includes segment-by-segment quality estimation scores in addition to other useful project statistics such as word, character, placeholder and tag counts.