Audio annotation · Hinglish
Hinglish Audio Annotation
Labelling of existing audio: speaker diarisation, emotion, intent, events, language identification and segment-level quality tagging, against your label schema. This page covers how that works specifically for Hinglish, where intra-sentential switching means english words carry indian phonology, so english acoustic models mis-transcribe them.
- Language
- Hinglish (hi-Latn-IN)
- Dialects covered
- 4
- Typical programme
- 500-2,000 hours
- Cities
- Delhi, Gurugram, Noida
What changes when the language is Hinglish
The service specification stays constant across languages; the linguistics do not. For Hinglish, three things drive the design of a audio annotation programme.
- Intra-sentential switching means English words carry Indian phonology, so English acoustic models mis-transcribe them
- Dialect spread: Delhi corporate Hinglish, Mumbai Bambaiya, Call-centre register, Youth/social media register
- Hinglish is the code-mixing case itself. Typical urban customer-support speech is 30-60% English tokens embedded in Hindi grammar, with switching several times per utterance.
Technical specification
| Parameter | Standard |
|---|---|
| Label types | Diarisation, emotion, intent, events, language ID, quality |
| Granularity | Segment, utterance, or frame-level boundaries |
| Schema | Yours, or authored with you before work starts |
| Agreement | Multi-annotator overlap on a defined percentage |
| Tooling | Client tooling supported; otherwise our annotation workflow |
Hinglish cohort design
Recruit by switching behaviour, not by language proficiency. Screening recordings are used to confirm speakers switch naturally rather than performing one language.
| Dimension | Typical split | Why it matters for Hinglish |
|---|---|---|
| Gender | 50 / 50 | Pitch range differences change acoustic model behaviour; unbalanced cohorts bias recognition |
| Age | 18-25: 30%, 26-40: 40%, 41-60: 30% | Older speakers retain conservative Hinglish forms that younger urban speakers have lost |
| Region | Delhi NCR / Mumbai / Bengaluru and others | Dialect spread across 4 recognised varieties |
| Education | Mixed, including below-graduate | Prompt-reading fluency correlates with education and skews prosody |
| Condition | Studio / quiet room / field | Match the noise profile of your deployment |
Process
- Schema definition and edge-case documentation
- Annotator training and gold-set calibration
- Production annotation with gold items seeded in
- Adjudication of disagreements by a senior reviewer
- Delivery with per-label agreement statistics
Hinglish-specific quality rules
- Whether English tokens are written in Latin or transliterated into Devanagari must be fixed by rule, not left to annotators
- Language-ID tagging per token is required for training but is skipped by most vendors
- Ambiguous words shared by both languages need an explicit tie-break rule
Gold items are seeded throughout production so drift is caught during the run, not at delivery.
Deliverables
- Labelled data in your schema
- Gold set and calibration results
- Per-label agreement statistics
- Edge-case log
Worked example
A representative Hinglish audio annotation engagement: 500 hours from 1,000 speakers, 50/50 gender, ages 18-45, spread across Delhi, Gurugram, Noida, recorded to the specification above and delivered in WAV with a per-utterance manifest.
Timeline: Scoped per label complexity; simple diarisation runs at roughly 3-5x real time.
Where this data is missing today
Almost no public corpus contains genuine intra-sentential Hindi-English switching with per-token language tags. This is the highest-value gap for anyone building Indian conversational AI.
Frequently asked
How much does Hinglish audio annotation cost?
Priced per delivered hour or unit against a written spec. The cost drivers for Hinglish are dialect spread, demographic narrowness and recording condition, in that order.
Which Hinglish dialects are included?
By default Delhi corporate Hinglish, Mumbai Bambaiya, Call-centre register, Youth/social media register and others, tagged per speaker. You can also commission a single-dialect corpus if you are targeting one region.
Can you deliver Hinglish data in our format?
Yes. Labelled data in your schema is the default, but naming, schema and directory structure follow your pipeline.
How long does a Hinglish programme take?
Scoped per label complexity; simple diarisation runs at roughly 3-5x real time.
Request a Hinglish audio annotation quote
Hours, speakers, dialects, deadline. Send what you have.