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Voice recording · Machine Translation

Voice Recording for AI Training for Machine Translation

Studio voice recording built for model training rather than broadcast: controlled acoustics, consistent mic distance, and reproducible session parameters across every speaker. Applied to machine translation, the specification is driven by one thing: human adequacy and fluency scores.

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Abstract visualisation of translation between two Indian languages — Voice Recording for AI Training for Machine Translation
Service
Voice recording
Use case
Machine Translation
Primary metric
Human adequacy and fluency scores
01

Required data profile

  • Sentence-aligned parallel corpora
  • Register-matched to your product
  • Enforced terminology glossary
Voice recording — Machine Translation · written into the SOW before recordingSample rate48 kHzBit depth24-bitMicrophoneLarge-diaphragm condenser, fixed distance, pop filterRoomTreated booth, RT60 under 0.3sProcessingNone. No compression, EQ, or noise reduction on delivered a…Your values replace ours rather than being converted after delivery.
02

Technical specification

ParameterStandard
Sample rate48 kHz
Bit depth24-bit
MicrophoneLarge-diaphragm condenser, fixed distance, pop filter
RoomTreated booth, RT60 under 0.3s
ProcessingNone. No compression, EQ, or noise reduction on delivered audio
Session length30-90 minutes per speaker, with breaks logged
Speaker recording scripted prompts for a speech data collection project — supporting voice recording for ai training for machine translation
Speaker recording scripted prompts for a speech data collection project
03

Process

  • Session template definition so every studio in the network records identically
  • Speaker briefing and pronunciation calibration
  • Take-level monitoring with immediate re-record on defect
  • Per-session technical report
  • Delivery with unprocessed masters
04

Metrics this feeds

  • Human adequacy and fluency scores
  • Terminology compliance rate
  • Back-translation divergence
05

Failure modes to design out

  • Pivoting everything through English
  • Post-edited machine output passed off as human translation

Delivered audio is never processed. Training pipelines should see the raw capture so augmentation stays under your control.

06

Deliverables

  • Unprocessed WAV masters
  • Session logs
  • Take-level metadata
  • Speaker consent records

Frequently asked

Is voice recording 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 voice recording for machine translation

Send the metric you need to move.

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