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Voice evaluation · हिन्दी

Hindi AI Voice Evaluation

Human evaluation of your speech models: MOS and preference testing for TTS, WER-in-context review for ASR, and native-speaker judgement on naturalness and intelligibility. 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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Evaluator scoring AI voice output against a rubric — Hindi AI Voice Evaluation
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 voice evaluation 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.
Voice evaluation — Hindi · written into the SOW before recordingTTSMOS (1-5), MUSHRA, and A/B preference protocolsASRError typing: substitution, deletion, insertion, code-switc…PanelNative speakers of the target variety, screened and calibra…Sample sizePowered per the effect size you need to detectReportingPer-item scores plus aggregate with confidence intervalsYour values replace ours rather than being converted after delivery.
02

Technical specification

ParameterStandard
TTSMOS (1-5), MUSHRA, and A/B preference protocols
ASRError typing: substitution, deletion, insertion, code-switch failure
PanelNative speakers of the target variety, screened and calibrated
Sample sizePowered per the effect size you need to detect
ReportingPer-item scores plus aggregate with confidence intervals
Data visualisation of studio and field recording coverage across India — supporting hindi ai voice evaluation
Data visualisation of studio and field recording coverage across India
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

  • Protocol design and sample-size calculation
  • Panel recruitment and calibration on reference items
  • Blind evaluation with attention checks
  • Statistical analysis
  • Report with per-error-type breakdown
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

Attention checks and reference anchors are embedded so unreliable raters are detected and excluded before analysis.

06

Deliverables

  • Raw per-rater scores
  • Aggregated results with confidence intervals
  • Error-type analysis
  • Recommended fix priorities
07

Worked example

A representative Hindi voice evaluation 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: 1-3 weeks per evaluation round.

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 voice evaluation 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. Raw per-rater scores is the default, but naming, schema and directory structure follow your pipeline.

How long does a Hindi programme take?

1-3 weeks per evaluation round.

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

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