In what ways do language translation technologies handle idiomatic expressions and slang, which often do not have direct equivalents in other languages?
How do professional human translators and machine translation systems complement each other in industry applications to ensure high-quality translations?
How is real-time language translation implemented in communication platforms, and what are the technological limitations that need to be addressed to improve the speed and accuracy of such systems?
What ethical considerations arise in the deployment of machine translation systems, and how can biases in training data affect the fairness and inclusivity of translations?
How does context play a role in achieving high-quality translations, and what techniques are used in machine translation to account for context beyond individual sentences?
What are the main challenges in achieving accurate translation for languages with complex grammatical structures or those with limited available data for training machine learning models?
How do neural machine translation (NMT) models improve upon traditional statistical machine translation (SMT) approaches in terms of accuracy and naturalness of the translated output?
