aidataservices.inAI data collection · India

Call-centre speech · LLM Evaluation

Call Centre Speech Data for LLM Evaluation

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 llm evaluation, the specification is driven by one thing: rubric scores with confidence intervals.

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Contact centre agents generating call centre speech data — Call Centre Speech Data for LLM Evaluation
Service
Call-centre speech
Use case
LLM Evaluation
Primary metric
Rubric scores with confidence intervals
01

Required data profile

  • Native-speaker rater panels per language
  • Rubric-based scoring with calibration
  • Overlapping assignments for agreement
Call-centre speech — LLM Evaluation · 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
Transcriber timestamping Indian language audio — supporting call centre speech data for llm evaluation
Transcriber timestamping Indian language audio
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

  • Rubric scores with confidence intervals
  • Inter-rater agreement
  • Failure-mode distribution
05

Failure modes to design out

  • Raters who are fluent but not native in the variety
  • Rubrics written in English and applied to non-English output without localisation

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 llm evaluation?

It covers native-speaker rater panels per language. Most llm evaluation 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 llm evaluation

Send the metric you need to move.

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