An AI tool that analyzes the voice of both the customer and the support agent during a call in real-time. It detects emotional cues like frustration or satisfaction and provides live coaching tips to the agent on a private dashboard (e.g., 'Customer tone is negative. Try expressing more empathy.')
Contact centre agents handle difficult calls all day, often with limited coaching support. Team leaders can only listen to a small sample of calls, and feedback usually arrives days later, long after the moment when a different phrase could have calmed a frustrated customer. New agents in particular struggle to notice escalating frustration while also navigating systems and policies, and a call that could have been rescued ends in a complaint.
Call centre emotion detection AI provides in-the-moment support. It transcribes the conversation in real time, analyses word choice and vocal cues such as pace and volume, and estimates when the customer's tone is becoming negative. The agent sees discreet prompts on screen, like acknowledging the problem or explaining next steps. The technology is imperfect at reading emotion, and it can feel intrusive to staff, so it works best as a coaching aid with clear boundaries rather than a performance score.
Audio from the telephony or contact centre platform is streamed to a speech-to-text service, producing a live transcript for both customer and agent channels.
Sentiment and tone models analyse words, pace, pitch changes and interruptions to estimate whether the conversation is becoming more positive or more negative.
When negative sentiment rises past a set level, a coaching prompt appears in the agent's side panel, drawn from phrases approved by team leaders.
Team leaders can see live call sentiment across the floor and choose to offer help or join a call when a conversation is escalating.
After the call, the transcript and sentiment timeline feed coaching sessions, focusing on examples of effective de-escalation rather than individual scores.
During a support call, the AI detects rising frustration in the customer's voice. It privately prompts the agent on their screen with 'Show empathy now: Try saying, I understand how frustrating that must be.' The agent uses the tip, de-escalating the situation and improving the customer's experience.
Speech-to-Text, Tone & Sentiment Analysis, Real-time Transcription
Call recording and real-time monitoring are covered by state and territory surveillance and listening devices laws, which differ, and federal telecommunications law, so inform customers at the start of the call and check requirements for each state you operate in. Transcripts contain personal information under the Privacy Act 1988, and callers may disclose health or financial details, so control access and retention. Monitoring employees may fall under workplace surveillance legislation in NSW and the ACT, and using emotion scores in performance management raises Fair Work and fairness issues. Be cautious with emotion inference; accuracy varies by accent, culture and speech differences.
This solution requires careful evaluation of cost-benefit ratio. Consider implementation only after thorough analysis and risk assessment.
It is better at detecting clear changes, like raised voices or repeated complaints, than subtle feelings. Accuracy varies with audio quality, accents and speaking styles. Treat outputs as signals to pay attention, not as facts about how a customer feels, and review a sample of flagged calls to understand where it goes wrong.
They may, unless the rollout is handled openly. Explain what is analysed, who sees it and how it will be used, ideally in writing. Many centres limit real-time prompts to the agent's own screen and use aggregated data only for coaching, which helps staff see the tool as support rather than surveillance.
Two to four weeks for a pilot team is common, provided your contact centre platform supports audio streaming. Time goes into integration, tuning transcription for local terms, writing coaching prompts with team leaders, staff consultation and a supervised trial before wider rollout.
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