Speech data collection · Hinglish
Hinglish Speech Data Collection
Recruited-speaker speech corpora recorded to a written specification: scripted prompts, spontaneous monologue, or both, with full speaker metadata. 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 speech data collection 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 |
|---|---|
| Sample rate | 48 kHz capture, delivered at 48/16 kHz as required |
| Bit depth | 24-bit capture, 16-bit PCM delivery |
| Format | WAV (PCM), one file per utterance or per session |
| Channels | Mono per speaker; multi-channel on request |
| Noise floor | Studio sessions below -50 dBFS; field sessions specified per project |
| Clipping | Zero tolerance; clipped takes are re-recorded, not repaired |
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
- Requirement lock: languages, hours, speaker count, demographic quotas, recording conditions
- Prompt design and linguistic review by native reviewers
- Speaker recruitment and screening against quota, with consent capture
- Recording sessions with real-time level and prompt-coverage monitoring
- Automated technical QA on every file (SNR, clipping, duration, silence)
- Native-speaker content QA on a defined sample, escalating to 100% on failure
- Packaging, manifest generation and delivery
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
Every file passes automated technical checks. Content QA is sampled at 10% by default and raised per batch when the failure rate crosses the agreed threshold.
Deliverables
- Audio files in the agreed format and naming convention
- Per-utterance manifest (speaker ID, prompt ID, duration, condition)
- Speaker metadata: age band, gender, region, dialect, education band
- Consent records mapped to speaker IDs
- QA report with pass rates and rejection reasons
Worked example
A representative Hinglish speech data collection 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: Typical: 3-6 weeks for 100-500 hours in a single language; multi-language programmes run in parallel.
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 speech data collection 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. Audio files in the agreed format and naming convention is the default, but naming, schema and directory structure follow your pipeline.
How long does a Hinglish programme take?
Typical: 3-6 weeks for 100-500 hours in a single language; multi-language programmes run in parallel.
Request a Hinglish speech data collection quote
Hours, speakers, dialects, deadline. Send what you have.