Adapting ChatGPT for Real-Time Interactive Machine Translation: Challenges and Solutions

Abstract

The evolution of machine translation (MT) has seen significant advancements with the advent of transformer-based models like GPT-3. ChatGPT, a variant optimized for conversational contexts, presents new opportunities for real-time interactive MT. However, integrating ChatGPT into real-time MT systems poses several challenges. This paper explores the hurdles faced when adapting ChatGPT for interactive MT and proposes solutions to address these issues. We focus on latency reduction, contextual coherence, user interaction handling, and resource management to enhance the efficacy of real-time translation systems.