Developer building real-time meeting translation tool shares key engineering lessons

A developer has spent several months building a real-time translation tool for online meetings, initially expecting speech recognition and translation API selection to be the main hurdles. The biggest challenge turned out to be latency, as subtitles appearing even two to three seconds late make the experience feel broken to users. The developer found that translation quality also suffered because spoken language is fragmented and informal, causing even high-performing AI models to struggle when input arrives in partial sentences. This led to rethinking the entire pipeline, including audio capture, incremental speech recognition, buffering strategies, and subtitle rendering. The project highlighted that real-time AI applications require constantly balancing latency, stability, and accuracy — improving one often degrades another.