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Multilingual collection · हिन्दी

Hindi Multilingual Data Collection

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. This page covers how that works specifically for Hindi, where four-way stop contrast (voiced/voiceless x aspirated/unaspirated) that collapses in models trained on english-first acoustic units.

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Diverse Indian speakers waiting for multilingual data collection sessions — Hindi Multilingual Data Collection
Language
Hindi (hi-IN)
Dialects covered
7
Typical programme
500-2,000 hours
Cities
Delhi, Lucknow, Jaipur
01

What changes when the language is Hindi

The service specification stays constant across languages; the linguistics do not. For Hindi, three things drive the design of a multilingual collection programme.

  • Four-way stop contrast (voiced/voiceless x aspirated/unaspirated) that collapses in models trained on English-first acoustic units
  • Dialect spread: Khari Boli, Awadhi, Braj, Bhojpuri-influenced Hindi
  • Urban Hindi speech is Hinglish in practice. Expect 15-40% English tokens in spontaneous speech: numbers, brands, technology terms, and whole clause switches. Any Hindi corpus that excludes English tokens will not match production traffic.
Multilingual collection — Hindi · 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
Voice artist recording training data for an AI voice model — supporting hindi multilingual data collection
Voice artist recording training data for an AI voice model
03

Hindi cohort design

Largest recruitment pool in the network. A 1,000-speaker Hindi cohort with balanced gender and 18-45 age bands is typically fielded across four cities to avoid a single-city accent bias.

DimensionTypical splitWhy it matters for Hindi
Gender50 / 50Pitch range differences change acoustic model behaviour; unbalanced cohorts bias recognition
Age18-25: 30%, 26-40: 40%, 41-60: 30%Older speakers retain conservative Hindi forms that younger urban speakers have lost
RegionUttar Pradesh / Bihar / Madhya Pradesh and othersDialect spread across 7 recognised varieties
EducationMixed, including below-graduatePrompt-reading fluency correlates with education and skews prosody
ConditionStudio / quiet room / fieldMatch the noise profile of your deployment
04

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
05

Hindi-specific quality rules

  • Inconsistent Devanagari vs romanised spelling for the same English loan word
  • Nukta characters (क़ ख़ ग़ ज़ फ़) applied inconsistently by transcribers
  • Numerals: whether to write digits, Devanagari numerals, or spelled-out words must be fixed in the style guide up front
  • Honorific verb forms create long agreement chains that annotators shorten unless the guide forbids it

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
07

Worked example

A representative Hindi multilingual collection engagement: 500 hours from 1,000 speakers, 50/50 gender, ages 18-45, spread across Delhi, Lucknow, Jaipur, recorded to the specification above and delivered in WAV with a per-utterance manifest.

Timeline: 6-12 weeks for a multi-language programme, depending on the smallest-pool language in scope.

08

Where this data is missing today

Public Hindi corpora skew heavily towards read newspaper text from educated urban speakers in Delhi and NCR. Rural Bihar and eastern UP speech, elderly speakers, and low-literacy speakers reading prompts aloud are largely absent.

Frequently asked

How much does Hindi multilingual collection cost?

Priced per delivered hour or unit against a written spec. The cost drivers for Hindi are dialect spread, demographic narrowness and recording condition, in that order.

Which Hindi dialects are included?

By default Khari Boli, Awadhi, Braj, Bhojpuri-influenced Hindi and others, tagged per speaker. You can also commission a single-dialect corpus if you are targeting one region.

Can you deliver Hindi data in our format?

Yes. Per-language datasets in one schema is the default, but naming, schema and directory structure follow your pipeline.

How long does a Hindi programme take?

6-12 weeks for a multi-language programme, depending on the smallest-pool language in scope.

Request a Hindi multilingual collection quote

Hours, speakers, dialects, deadline. Send what you have.

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