Free Hindi speech data sample

• Hindi audio from at least four speakers with a mixed gender and age spread
• Coverage of Khari Boli, Awadhi, Braj where your spec calls for dialect breadth
• Verbatim transcripts in Devanagari, 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 Hindi code-mixing is transcribed: 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.
• Check the transcription convention against your tokeniser — Inconsistent Devanagari vs romanised spelling for the same English loan word is the usual failure point
• Confirm the metadata is complete enough to filter and stratify by

Hindi has roughly 528 million speakers across Uttar Pradesh, Bihar, Madhya Pradesh, and models trained on generic multilingual data typically fail on the same things each time.

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.

• Phonetics your acoustic model may not have seen: Four-way stop contrast (voiced/voiceless x aspirated/unaspirated) that collapses in models trained on English-first acoustic units
• Utterance types worth sampling separately: Scripted prompt reading (phonetically balanced sentence sets), Wake-word and command-and-control utterances, Digit strings, dates, amounts, and Indian address formats
• Recording geography in the sample: Delhi, Lucknow, Jaipur

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.

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.