Your Conversational AI Glossary
Speech-to-Text (STT)
What is Speech-to-Text
Speech-to-Text (STT) is a technology that converts spoken language into written text. Also known as automatic speech recognition (ASR), it enables machines to “listen” and transcribe what’s being said in real time — making it essential for voice assistants, transcription services, and AI receptionists.
How Does Speech-to-Text Work?
STT uses a combination of machine learning, linguistics, and acoustic modeling to recognize words from voice input. It works in stages:
Audio Input: Captures voice through a microphone or phone call
Feature Extraction: Breaks speech into audio features (pitch, tone, rhythm)
Pattern Recognition: Compares sounds to known language patterns
Transcription: Converts the result into readable text
Advanced STT systems are trained on vast datasets in multiple languages, accents, and speaking styles to improve accuracy over time.
Why Is Speech-to-Text Important?
Speech-to-Text plays a vital role in voice-based AI applications, including:
AI receptionists and voice bots
Live transcription services (e.g., for meetings or courtrooms)
Voice-controlled apps and smart devices
Accessibility tools for people with hearing impairments
For businesses, it allows hands-free input, real-time analysis of conversations, and automated call summaries — all of which boost efficiency and user experience.
Examples of Speech-to-Text Use Cases
A virtual receptionist transcribes caller intent before responding
Real-time captioning during webinars or interviews
Voice assistants transcribing spoken commands
Converting voicemails into text messages
Related Terms
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