What is Sentiment Analysis?
Sentiment analysis is the AI technique of detecting emotional tone and attitude from text or speech. In voice AI, it goes beyond text: it also analyzes vocal cues like pitch, speed, volume, and pauses to gauge caller frustration, satisfaction, or urgency.
How Sentiment Analysis works
Text based sentiment analysis classifies input as positive, negative, or neutral using trained models. Voice based sentiment analysis adds acoustic features: a raised voice, faster speech, longer pauses, and changes in pitch all signal emotional states. Real time sentiment tracking allows voice AI systems to adjust their responses (slower pace for frustrated callers, more empathetic language) or escalate to human agents when sentiment drops below a threshold.
Why Sentiment Analysis matters for enterprise
Sentiment analysis enables proactive customer experience management. A collections call that detects rising frustration can offer a payment plan before the caller hangs up. A sales call that detects high interest can fast track the lead to a human closer. It also provides aggregate sentiment data for QA and training purposes.
How ARCA handles Sentiment Analysis
ARCA performs real time sentiment analysis during calls, using both text and voice signals to adapt conversation tone and trigger escalation when needed.
See how ARCA uses sentiment analysis in practice.
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