aidataservices.inAI data collection · India

Call-centre speech · Speaker Diarisation

Call Centre Speech Data for Speaker Diarisation

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 speaker diarisation, the specification is driven by one thing: diarisation error rate.

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Contact centre agents generating call centre speech data — Call Centre Speech Data for Speaker Diarisation
Service
Call-centre speech
Use case
Speaker Diarisation
Primary metric
Diarisation error rate
01

Required data profile

  • Per-speaker isolated channels with a mixed reference
  • Genuine overlap preserved
  • Turn-level ground truth
Call-centre speech — Speaker Diarisation · 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
Voice artist recording training data for an AI voice model — supporting call centre speech data for speaker diarisation
Voice artist recording training data for an AI voice model
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

  • Diarisation error rate
  • Overlap detection recall
  • Speaker-count accuracy
05

Failure modes to design out

  • Overlap edited out during recording
  • Single-channel-only capture leaving no reliable ground truth

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 speaker diarisation?

It covers per-speaker isolated channels with a mixed reference. Most speaker diarisation 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 speaker diarisation

Send the metric you need to move.

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