Overview
Technology that converts a caller's spoken words into text that voice agents can understand and process in real-time.
Why it matters
When your voice agent can't understand accents, background noise interferes with calls, or speech isn't being transcribed accurately.
How it works
Automatic Speech Recognition (ASR) works by processing voice data through multiple stages of the AI pipeline, from recognition through understanding to response generation.
Common issues
Hamming's testing reveals ASR accuracy degrades significantly with background noise, accents, and domain-specific terminology. Hamming tests ASR performance across multiple scenarios to identify weaknesses before production deployment. Regular testing with diverse audio samples is essential for maintaining ASR quality.
Implementation guide
Follow Hamming's approach: Test with 50+ recorded utterances, include samples with background noise, validate across different accents and speaking speeds, and monitor ASR latency alongside accuracy metrics.