Automatic speech recognition is the technology that converts spoken language into text. ASR is the first step in any voice AI pipeline, transforming audio input into words that can be processed by language models.
How does ASR work?
Modern ASR systems use deep learning models trained on massive amounts of speech data. When audio arrives, the system analyzes acoustic features and predicts the most likely sequence of words. Advanced systems handle accents, background noise, and natural speech patterns including hesitations and corrections.
ASR can operate in real-time (streaming) or process complete recordings (batch). For voice agents, streaming ASR is essential because the system must understand callers as they speak rather than waiting for complete sentences.
Why does ASR matter?
ASR accuracy directly impacts everything downstream. If the system mishears “cancel” as “can sell,” the entire response will be wrong. High-quality ASR handles diverse speakers, noisy environments, and domain-specific vocabulary. Poor ASR creates frustrating experiences where callers must repeat themselves.
ASR in practice
A medical practice’s voice agent uses ASR optimized for healthcare terminology. When a patient says “I need to refill my lisinopril prescription,” the ASR correctly transcribes the medication name rather than guessing at a similar-sounding word. This accuracy enables the agent to process the refill request without clarification.