aidataservices.inAI data collection · India

Call-centre speech · Speech Emotion Recognition

Call Centre Speech Data for Speech Emotion Recognition

Simulated and consented real-world contact-centre audio in Indian languages, recorded over telephony-grade channels so it matches the bandwidth your production system actually sees. Applied to speech emotion recognition, the specification is driven by one thing: per-class f1.

Request a dataset quoteReply within one working day
Contact centre agents generating call centre speech data — Call Centre Speech Data for Speech Emotion Recognition
Service
Call-centre speech
Use case
Speech Emotion Recognition
Primary metric
Per-class F1
01

Required data profile

  • Elicited and natural emotional speech
  • Multi-rater emotion labels with adjudication
  • Balanced across emotion classes
Call-centre speech — Speech Emotion Recognition · written into the SOW before recordingChannel8 kHz narrowband telephony plus 48 kHz reference where requ…CodecG.711 / Opus simulated to match your stackStructureAgent and customer on separate channelsScenariosBilling, delivery, KYC, recharge, collections, support, sal…EmotionNeutral, frustrated and escalated variants on requestYour values replace ours rather than being converted after delivery.
02

Technical specification

ParameterStandard
Channel8 kHz narrowband telephony plus 48 kHz reference where required
CodecG.711 / Opus simulated to match your stack
StructureAgent and customer on separate channels
ScenariosBilling, delivery, KYC, recharge, collections, support, sales
EmotionNeutral, frustrated and escalated variants on request
Audio waveforms being prepared as ASR training data — supporting call centre speech data for speech emotion recognition
Audio waveforms being prepared as ASR training data
03

Process

  • Scenario library built from your call taxonomy
  • Agent-side speakers briefed on your script and tone
  • Recording over the specified codec path
  • Transcription with intent and outcome labels
  • Delivery with per-scenario counts
04

Metrics this feeds

  • Per-class F1
  • Inter-rater agreement on labels
  • Escalation detection latency
05

Failure modes to design out

  • Acted emotion only
  • Single-rater labels on an inherently subjective task

Narrowband is simulated at capture time, not by downsampling clean studio audio, which would leave unrealistic artefacts.

06

Deliverables

  • Dual-channel call audio
  • Verbatim transcripts
  • Intent, outcome and sentiment labels
  • Scenario coverage matrix

Frequently asked

Is call-centre 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 call-centre speech for speech emotion recognition

Send the metric you need to move.

Request a dataset quote