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We present a computational application to facilitate text chat-based communication between people with different cultural and language background. We focus on end-to-end communication between people with rudimentary and intermediary knowledge of the second language using computer support rather than using a simple connection with automated computer translation. Through a user-centered design process, involving three increasingly hifidelity prototypes, we created a system that allows users who speak different languages to send text messages between them that begins with an automated translation of their message that does a partial translation but normally has words that are not translated well. These poorly translated words are then searched for in a common sense knowledge base for the sender's culture that contains meanings gleaned from a large open source initiative to collect common sense knowledge. Using these additional concepts and words coupled to a translator, the user can select from a list of translations those that are better suited to the intention of the message. We illustrate the usefulness of our approach empirically to show that users find the augmented translated messages are culturally sensitive and provide better communication experiences than without it. Our study used messaging between Portuguese (Brazilian) and English speakers.