Speech data collection · Machine Translation
Speech Data Collection for Machine Translation
Recruited-speaker speech corpora recorded to a written specification: scripted prompts, spontaneous monologue, or both, with full speaker metadata. Applied to machine translation, the specification is driven by one thing: human adequacy and fluency scores.
- Service
- Speech data collection
- Use case
- Machine Translation
- Primary metric
- Human adequacy and fluency scores
Required data profile
- Sentence-aligned parallel corpora
- Register-matched to your product
- Enforced terminology glossary
Technical specification
| Parameter | Standard |
|---|---|
| Sample rate | 48 kHz capture, delivered at 48/16 kHz as required |
| Bit depth | 24-bit capture, 16-bit PCM delivery |
| Format | WAV (PCM), one file per utterance or per session |
| Channels | Mono per speaker; multi-channel on request |
| Noise floor | Studio sessions below -50 dBFS; field sessions specified per project |
| Clipping | Zero tolerance; clipped takes are re-recorded, not repaired |
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
Metrics this feeds
- Human adequacy and fluency scores
- Terminology compliance rate
- Back-translation divergence
Failure modes to design out
- Pivoting everything through English
- Post-edited machine output passed off as human translation
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.
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 machine translation?
It covers sentence-aligned parallel corpora. Most machine translation 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 machine translation
Send the metric you need to move.