Find the moments worth a listen
IdentityCall estimates emotion for each segment of a call from the audio, so reviewers can see where a customer’s tone shifted and open that part of the call.
A transcript tells you what was said. It does not tell you that the customer was already frustrated by the second sentence, or that the agent stayed calm under pressure. Tone carries signal that text alone misses.
IdentityCall analyzes emotion acoustically, per dialogue segment, and labels each customer turn with an estimated emotion. These are model estimates, not confirmed emotions. They point reviewers at segments to check; they are not a judgment of anyone on the call.
Why text sentiment is not enough
Tone lives in the audio
The same words can be neutral or hostile depending on delivery. Analyzing text alone throws away the delivery.
Averages hide the moment
A single sentiment score for a whole call hides where it went wrong. You need to see the turn where frustration appeared.
Follow-ups get missed
A customer who sounded frustrated and got no follow-up is easy to lose track of. Without a way to find those calls, nobody calls back.
How emotion analytics works in IdentityCall
Emotion per dialogue segment
IdentityCall estimates emotion from the audio for each segment of the conversation, so you can see where tone shifted, not just an overall label.
Acoustic, not just text
Estimates come from how things were said, which text-based sentiment cannot see.
Trends by category and project
Estimates roll up by call category and project, so you can see which topics most often carry frustration cues.
Used to prioritize review
Emotion estimates help decide which calls a reviewer opens first. They are not a prediction of cancellation and they do not score agents.
What you get
Emotion estimates for each segment of every submitted call- Acoustic analysis that reads delivery, not just words
- Trends by call category and project
- A list of calls with frustration cues to follow up
- The exact turn to open when reviewing a call
- Context next to QA scores, not a score of its own
Frequently asked questions
Is this text sentiment or voice emotion?
IdentityCall estimates emotion acoustically, from the audio of the call, per dialogue segment. That captures tone and delivery, which text-only sentiment cannot.
How granular is it?
Emotion is estimated for each dialogue segment, meaning each turn in the conversation, so you can pinpoint where tone changed rather than seeing one score for the whole call.
Can I use emotion estimates to evaluate agents?
Use them to understand the customer’s experience and to pick calls to review. Do not use them to assess employees: inferring employees’ emotions at work is a prohibited practice under the EU AI Act, with narrow exceptions. Agent QA in IdentityCall runs on the transcript against your rubric.
Does emotion feed QA scores?
Emotion estimates can add context to a goal about the customer’s experience, for example whether a complaint was resolved. They are estimates, so check the segment before acting on one.
Related
Find the calls worth a closer listen
See how IdentityCall estimates emotion per segment and points reviewers at the right moment.
