Neural Machine Translation on Employee-Customer Interactions

Abstract

Communication between different cultures is a problem which has plagued humanity for centuries. However, due to the countless complexities of language and culture, beyond human translation there has never been a reliable method to translate between any two given languages, except for human translation. In this study we have tested two commonly used models for machine translation and have tried to analyze their effectiveness and some possible limitations in their capabilities while attempting to translate conversations and interactions between employees and clients of various retail and customer service interactions