When a voice agent misbehaves, most teams blame:
❌ The LLM
❌ The prompt
❌ The agent
The problem usually started when the audio was still audio.
Bad audio breaks voice AI in two ways:
1. Higher word error rate (WER)
2. Agents that interrupt themselves or stop talking because they mistake background noise for a human speaker
Here's the catch:
A perfect transcript doesn't guarantee a good voice agent.
Your model can recognize every word...and still respond to the wrong speaker or the wrong interruption.
AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
LLM — A large language model — the neural network behind tools like Claude and ChatGPT, trained on huge amounts of text to predict what comes next.
Why it matters
A lower word error rate will not stop an AI agentAn AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.Full definition → from answering the television or interrupting itself. Primary speaker identification, which is not the same as diarization, is what tells the agent which voice in a changing room to follow.
