Custom collection and annotation
Emotion-labeled conversational speech for agents that hear frustration
A voice agent that answers correctly while the caller gets angrier is still failing. Turn-level affect labels on natural conversation give an agent something to detect, and give you something to evaluate it against.
Free sample: Name the language and the interaction type. The team labels a representative conversational excerpt with your categories and sends it manually within 48 hours, free of charge.
Collection specification
- Discrete labels
- Anger, disgust, fear, happiness, sadness, surprise, and neutral per turn across both sides of the exchange
- Dimensional labels
- Valence and arousal on the same turns, for models that need a trend rather than a class
- Speech type
- Spontaneous paired conversation, not read prompts, so the affect is occurring rather than performed
- Handoff points
- Turns annotated where a human would escalate, usable as an evaluation target for handoff timing
- Intent
- Dialogue acts or your own taxonomy, tracked separately from affect
- Coverage
- Language, accent, age, device, and noise quotas set per project
- Pricing
- Custom, scoped to your conditions
Acted emotion teaches an agent to detect acting
Most openly available emotion corpora are performed: actors reading set sentences in a named emotion. Models trained on them learn a clean, exaggerated version of affect that real callers rarely produce, and they degrade the moment a genuinely irritated person speaks in a flat voice.
Labeling spontaneous conversation is harder and the agreement figures are lower, which is exactly why we publish them. What you get in return is affect that occurred rather than affect that was staged.
Evaluation needs the same labels as training
Detecting frustration is only half the requirement. The other half is whether the agent did anything sensible about it, and that cannot be measured without labeled turns to measure against.
The same annotation pass supports both, so an evaluation set and a training set share one schema rather than being reconciled after the fact.
This offer is not the right fit when
- You need a ready trained emotion classifier rather than labeled data.
- You only want scripted, acted emotional speech.
- You want text sentiment labels with no audio.
Get a free labeled sample
- Your details
- Your project
- Verify
Three short steps. The team then follows up manually within 48 hours, and confirms volume, rights, QA, and delivery if you want the scope priced.
Would rather talk it through first? Talk through your label taxonomy
Prepare the brief
Bring a specification your vendors can price consistently
Use the free worksheet to define coverage, rights, delivery fields, held-out rules, and acceptance tests before requesting a collection plan.
Buyer documentation
Specimen data card and provenance structure, evaluation brief template, and acceptance and held-out questions.
Related services
Guides for this decision
Want to talk through your taxonomy first? Category sets, dimensional scales, and agreement thresholds are usually a conversation, not a form field. Book a short call to work through the taxonomy and conditions the labels need to hold up under.