Offline Speech Translation

Offline speech translation (OST) aims to accurately and efficiently convert spoken language into another written language without the real-time constraints of simultaneous translation. Current research focuses on adapting existing offline machine translation and automatic speech recognition models for OST, often employing techniques like large language model integration, optimal transport for aligning speech and text representations, and novel training paradigms to optimize the balance between translation quality and latency. These advancements are improving the accuracy and efficiency of OST systems, impacting fields like multilingual communication and accessibility by enabling the creation of high-quality, offline translation tools.