Free Hinglish speech data sample

• Hinglish audio from at least four speakers with a mixed gender and age spread
• Coverage of Delhi corporate Hinglish, Mumbai Bambaiya, Call-centre register where your spec calls for dialect breadth
• Verbatim transcripts in Devanagari + Latin, with a romanised parallel transcript on request
• Per-file metadata: speaker ID, age band, gender, district, device, environment and SNR
• A short QA report showing how the files were checked before they were sent

The sample is only useful if it looks like the data you would actually buy. Send the spec you would put in a purchase order and we record against that.

• Run it through your existing ASR or TTS pipeline and read the error breakdown by speaker and dialect
• Check how Hinglish code-mixing is transcribed: 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.
• Check the transcription convention against your tokeniser — Whether English tokens are written in Latin or transliterated into Devanagari must be fixed by rule, not left to annotators is the usual failure point
• Confirm the metadata is complete enough to filter and stratify by

Hinglish has roughly 350 million speakers across Delhi NCR, Mumbai, Bengaluru, and models trained on generic multilingual data typically fail on the same things each time.

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.

• Phonetics your acoustic model may not have seen: Intra-sentential switching means English words carry Indian phonology, so English acoustic models mis-transcribe them
• Utterance types worth sampling separately: Simulated customer-support calls with natural switching, Two-party spontaneous conversation between colleagues, Voice-assistant commands with English app and brand names
• Recording geography in the sample: Delhi, Gurugram, Noida

Nothing automatic. If the sample works, we scope the full build against the same specification and quote a fixed price. If it does not, tell us what failed — that feedback is more useful to us than a polite no.

Recruit by switching behaviour, not by language proficiency. Screening recordings are used to confirm speakers switch naturally rather than performing one language.