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Kannada 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 Kannada, where north karnataka speech has markedly different intonation and lexicon from mysuru standard.

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Evaluator scoring AI voice output against a rubric — Kannada AI Voice Evaluation
Language
Kannada (kn-IN)
Dialects covered
5
Typical programme
250-1,000 hours
Cities
Bengaluru, Mysuru, Hubballi-Dharwad
01

What changes when the language is Kannada

The service specification stays constant across languages; the linguistics do not. For Kannada, three things drive the design of a voice evaluation programme.

  • North Karnataka speech has markedly different intonation and lexicon from Mysuru standard
  • Dialect spread: Bangalore urban, Mysuru (standard literary), Dharwad / North Karnataka, Mangaluru coastal
  • Bengaluru is a migration city: Kannada speech there is mixed with English, Hindi, Tamil and Telugu. Native-only Kannada cohorts recruited in Bengaluru are hard to fill without screening for years of residence.
Voice evaluation — Kannada · 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
Annotators writing prompts and responses for LLM training data — supporting kannada ai voice evaluation
Annotators writing prompts and responses for LLM training data
03

Kannada cohort design

Screen Bengaluru participants for native fluency and years of Karnataka residence; otherwise the cohort drifts towards second-language Kannada.

DimensionTypical splitWhy it matters for Kannada
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 Kannada forms that younger urban speakers have lost
RegionKarnataka / parts of Maharashtra, Tamil Nadu and Andhra Pradesh and othersDialect spread across 5 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

Kannada-specific quality rules

  • Northern lexical items replaced with standard equivalents
  • Inconsistent transliteration of English technical terms
  • Sandhi in connected speech transcribed as separate words by some annotators and joined by others

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 Kannada voice evaluation engagement: 250 hours from 500 speakers, 50/50 gender, ages 18-45, spread across Bengaluru, Mysuru, Hubballi-Dharwad, 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

Mysuru/Bengaluru standard dominates. North Karnataka (Dharwad, Kalaburagi) and coastal Mangaluru speech are barely represented in any public corpus.

Frequently asked

How much does Kannada voice evaluation cost?

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

Which Kannada dialects are included?

By default Bangalore urban, Mysuru (standard literary), Dharwad / North Karnataka, Mangaluru coastal and others, tagged per speaker. You can also commission a single-dialect corpus if you are targeting one region.

Can you deliver Kannada 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 Kannada programme take?

1-3 weeks per evaluation round.

Request a Kannada voice evaluation quote

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

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