Conversational speech · Speech Emotion Recognition
Conversational Speech Data for Speech Emotion Recognition
Natural two-party and multi-party conversation recorded with separate channels per speaker, covering the overlaps, interruptions and turn-taking that scripted data never produces. Applied to speech emotion recognition, the specification is driven by one thing: per-class f1.
- Service
- Conversational speech
- Use case
- Speech Emotion Recognition
- Primary metric
- Per-class F1
Required data profile
- Elicited and natural emotional speech
- Multi-rater emotion labels with adjudication
- Balanced across emotion classes
Technical specification
| Parameter | Standard |
|---|---|
| Channels | One channel per speaker, time-aligned |
| Duration | 15-60 minutes per conversation |
| Topics | Scenario cards, free topics, or your domain scripts |
| Overlap | Preserved and tagged, never edited out |
| Metadata | Relationship between speakers, familiarity, topic, setting |
Process
- Scenario design so conversations stay on-domain without becoming scripted
- Speaker pairing by familiarity level as specified
- Multi-channel recording with per-speaker isolation
- Diarisation-ready packaging
- Verbatim transcription with speaker turns and overlap tags
Metrics this feeds
- Per-class F1
- Inter-rater agreement on labels
- Escalation detection latency
Failure modes to design out
- Acted emotion only
- Single-rater labels on an inherently subjective task
Conversations are checked for naturalness, not just audio quality. Sessions that drift into reading are rejected.
Deliverables
- Per-speaker channels plus mixed reference
- Turn-level transcripts
- Overlap and backchannel tags
- Conversation metadata
Frequently asked
Is conversational speech the right service for speech emotion recognition?
It covers elicited and natural emotional speech. Most speech emotion recognition programmes combine it with at least one other service; we will say so in the scope rather than selling one line item.
What languages are available?
All 14 languages in the network plus Indian English accent bands.
How is the evaluation set handled?
Collected first, from speakers disjoint from the training cohort, so improvement is measurable.
Scope conversational speech for speech emotion recognition
Send the metric you need to move.