LINZO: An AI-Powered Multilingual Communication System for Professional Meetings.

Abstract

As the global workforce continues to evolve rapidly, being able to share and communicate with colleagues in meetings in multiple languages for cross-cultural cooperation and decision making has never been more critical. This paper illustrates three whole-languages approaches that leverage AI- powered technologies (i.e. speech translation, speech to text transcription, and real-time captioning) to dissolve language barriers in a professional workplace and beyond. This study reviews those systems, proposes a conceptual prototype, and illustrates the ways that AI will harness Automatic Speech Recognition (ASR), Machine Translation, and Large Language Models (LLMs) to foster inclusivity, reduce latency, and improve the user experience. Recently released literature between 2018-2025 illustrates how combining real-time translation and user-centered design yield markedly improved comprehensibility, engagement, and productivity, as well as positive subjective user experiences from multilingual meetings.