aidataservices.inAI data collection · India

Call-centre speech · Accent Adaptation

Call Centre Speech Data for Accent Adaptation

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 accent adaptation, the specification is driven by one thing: per-accent wer spread.

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Contact centre agents generating call centre speech data — Call Centre Speech Data for Accent Adaptation
Service
Call-centre speech
Use case
Accent Adaptation
Primary metric
Per-accent WER spread
01

Required data profile

  • Accent-band balanced speech with substrate-language tags
  • Matched content across bands for controlled comparison
Call-centre speech — Accent Adaptation · 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
Two speakers recording natural conversational speech data — supporting call centre speech data for accent adaptation
Two speakers recording natural conversational speech 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-accent WER spread
  • Regression on the original accent set
05

Failure modes to design out

  • Treating Indian English as one accent
  • No substrate tagging, so the model cannot be evaluated per band

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 accent adaptation?

It covers accent-band balanced speech with substrate-language tags. Most accent adaptation 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 accent adaptation

Send the metric you need to move.

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