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Multilingual collection · Wake Word Detection

Multilingual Data Collection for Wake Word Detection

Parallel programmes across several Indian languages at once, run to one specification so the resulting datasets are comparable rather than a set of incompatible deliveries. Applied to wake word detection, the specification is driven by one thing: false accepts per hour.

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Smart speaker listening for a wake word in an Indian home — Multilingual Data Collection for Wake Word Detection
Service
Multilingual collection
Use case
Wake Word Detection
Primary metric
False accepts per hour
01

Required data profile

  • Thousands of speakers, few utterances each
  • Positive and hard-negative sets
  • Multiple distances and noise conditions
Multilingual collection — Wake Word Detection · written into the SOW before recordingLanguagesUp to 14 Indian languages plus Indian English in one progra…ConsistencyOne spec, one manifest schema, one QA standard across all l…BalancePer-language quotas set independently to match your deploym…ReportingSingle consolidated progress view across languagesYour values replace ours rather than being converted after delivery.
02

Technical specification

ParameterStandard
LanguagesUp to 14 Indian languages plus Indian English in one programme
ConsistencyOne spec, one manifest schema, one QA standard across all languages
BalancePer-language quotas set independently to match your deployment mix
ReportingSingle consolidated progress view across languages
Diverse Indian speakers waiting for multilingual data collection sessions — supporting multilingual data collection for wake word detection
Diverse Indian speakers waiting for multilingual data collection sessions
03

Process

  • Master specification written once and localised per language
  • Per-language linguistic review of prompts and guides
  • Parallel fielding across studio cities
  • Central QA applying identical thresholds
  • Consolidated delivery with per-language reports
04

Metrics this feeds

  • False accepts per hour
  • False reject rate per accent band
  • Performance at 3m and 5m
05

Failure modes to design out

  • Positives only, with no hard negatives
  • Close-mic-only capture
  • No accent-band tagging, so failures cannot be localised

The hardest language sets the timeline. Low-resource languages such as Assamese and Odia should start first.

06

Deliverables

  • Per-language datasets in one schema
  • Cross-language coverage report
  • Consolidated QA summary

Frequently asked

Is multilingual collection the right service for wake word detection?

It covers thousands of speakers, few utterances each. Most wake word detection 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 multilingual collection for wake word detection

Send the metric you need to move.

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