Speech-to-Text (STT)
AI technology that transcribes spoken audio into written text. Handles accents, background noise, multiple speakers, and technical jargon. Also called Automatic Speech Recognition (ASR).
Why it matters
STT turns talking into typed text, which saves enormous time whenever writing by hand is slow or impractical. It matters for anyone who dictates notes, captions videos, or transcribes interviews and meetings. Good STT handles accents, background noise, and multiple speakers, making spoken words searchable and shareable. It's also a big accessibility win, giving deaf and hard-of-hearing people real-time captions for calls and videos.
In practice
A journalist records a 40-minute interview, then runs it through an STT tool. Minutes later she has a full transcript that even labels who said what, despite some traffic noise and the subject's strong accent. Instead of replaying the audio for hours to find quotes, she searches the text for a keyword and jumps straight to the moment she needs. What was tedious manual work is now a quick, searchable document.
Related terms
AI Dubbing
Automated translation and re-voicing of audio/video content into other languages while preserving the original speaker's voice characteristics, timing, and emotional delivery.
AI Orchestration
Coordinating multiple AI models, tools, and data sources in a unified pipeline. An orchestration layer manages prompt routing, context passing, error handling, and output aggregation across different AI services.
API (Application Programming Interface)
A way for software applications to communicate with each other. AI APIs let developers integrate AI capabilities into their own applications programmatically.
Attention Mechanism
A technique that allows AI models to focus on the most relevant parts of input data when generating output. In language models, attention determines which words in a sentence are most important for understanding each other word.
Diffusion Model
A type of generative AI that creates images by gradually removing noise from a random starting point. Powers tools like Stable Diffusion, DALL-E, and Midjourney. Works by learning the reverse of a noise-adding process.
Distillation
A technique where a smaller 'student' model learns to replicate the behavior of a larger 'teacher' model. Produces compact models that retain most of the teacher's capability while being faster, cheaper, and deployable on smaller devices.