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Speech data collection · Accent Adaptation

Speech Data Collection for Accent Adaptation

Recruited-speaker speech corpora recorded to a written specification: scripted prompts, spontaneous monologue, or both, with full speaker metadata. Applied to accent adaptation, the specification is driven by one thing: per-accent wer spread.

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Speaker recording scripted prompts for a speech data collection project — Speech Data Collection for Accent Adaptation
Service
Speech data collection
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
Speech data collection — Accent Adaptation · written into the SOW before recordingSample rate48 kHz capture, delivered at 48/16 kHz as requiredBit depth24-bit capture, 16-bit PCM deliveryFormatWAV (PCM), one file per utterance or per sessionChannelsMono per speaker; multi-channel on requestNoise floorStudio sessions below -50 dBFS; field sessions specified pe…Your values replace ours rather than being converted after delivery.
02

Technical specification

ParameterStandard
Sample rate48 kHz capture, delivered at 48/16 kHz as required
Bit depth24-bit capture, 16-bit PCM delivery
FormatWAV (PCM), one file per utterance or per session
ChannelsMono per speaker; multi-channel on request
Noise floorStudio sessions below -50 dBFS; field sessions specified per project
ClippingZero tolerance; clipped takes are re-recorded, not repaired
Speaker reading a prompt script into a studio microphone — supporting speech data collection for accent adaptation
Speaker reading a prompt script into a studio microphone
03

Process

  • Requirement lock: languages, hours, speaker count, demographic quotas, recording conditions
  • Prompt design and linguistic review by native reviewers
  • Speaker recruitment and screening against quota, with consent capture
  • Recording sessions with real-time level and prompt-coverage monitoring
  • Automated technical QA on every file (SNR, clipping, duration, silence)
  • Native-speaker content QA on a defined sample, escalating to 100% on failure
  • Packaging, manifest generation and delivery
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

Every file passes automated technical checks. Content QA is sampled at 10% by default and raised per batch when the failure rate crosses the agreed threshold.

06

Deliverables

  • Audio files in the agreed format and naming convention
  • Per-utterance manifest (speaker ID, prompt ID, duration, condition)
  • Speaker metadata: age band, gender, region, dialect, education band
  • Consent records mapped to speaker IDs
  • QA report with pass rates and rejection reasons

Frequently asked

Is speech data collection 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 speech data collection for accent adaptation

Send the metric you need to move.

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