Speech-to-text models keep guessing wrong on the words that actually matter. Brand names become common words. Medical terms get butchered. Project codes vanish. AssemblyAI Universal-3.5 Pro fixed this with contextual prompting. Feed it your domain context and it stops guessing. Here's how it works 🧵👇

How contextual prompting works: Before transcription, you feed the model domain context. Prior patient notes for clinical audio. Meeting agendas for session recordings. Product catalogs for call centers. The model uses that context to guide what it writes. Stops guessing on domain-specific terms.

@python_spaces 项目代码被吞真的最烦，后面全靠猜

@python_spaces Context ending the guessing game, finally 🎯