Buy a Hindi spontaneous speech dataset

Speakers talk unscripted on prompted topics — describing a process, recounting an event, arguing a position — with a moderator who prompts but does not lead.

A 60-minute session covering six to eight topics, recorded continuously and segmented afterwards into utterances at natural pause boundaries.

60–70% of recorded time is accepted. Long silences, moderator speech and abandoned topics are cut in post, so recorded hours run well ahead of delivered hours. Budget for the gap.

• 16-bit PCM WAV audio, captured at 48 kHz / 24-bit and delivered at your target rate
• Verbatim Devanagari transcripts with utterance-level timestamps
• Filled-pause and false-start markers
• Segment offsets into the parent session file
• Topic label per segment
• Speech-rate and pause-density statistics per speaker
• Per-speaker metadata: age band, gender, region, dialect, education band, device
• Consent records mapped to speaker IDs and retained for audit
• Speaker-disjoint train / dev / test splits

The failure modes this style is prone to: speakers who dry up after a minute, leaving sessions that look complete by duration but are mostly silence

• Segment boundary review — bad boundaries produce truncated words that poison training more than they help
• Disfluency transcription consistency audited across transcribers, since conventions drift fast on this style
• Moderator speech confirmed absent from delivered segments
• Topic distribution checked per speaker so one dominant subject does not skew the language model

Bands, not a price list. A signed specification converts them into one fixed figure, and staged delivery lets you start training before the full corpus lands.

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.

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.

• Inconsistent Devanagari vs romanised spelling for the same English loan word
• Nukta characters (क़ ख़ ग़ ज़ फ़) applied inconsistently by transcribers
• Numerals: whether to write digits, Devanagari numerals, or spelled-out words must be fixed in the style guide up front
• Honorific verb forms create long agreement chains that annotators shorten unless the guide forbids it

• Perpetual, transferable licence covering model training, derivative models and commercial deployment
• Written informed consent from every speaker, retained and auditable
• Compliant with India's DPDP Act 2023 handling requirements and mapped to GDPR obligations for EU buyers
• No scraped, resold or re-licensed third-party audio in any delivery

• Send your specification or use the standard one above
• Receive a fixed scope, price and delivery schedule within one working day
• Optional paid pilot of 10-20 hours against the same spec
• Recruitment and recording begin on signature, with staged batches
• Acceptance testing per batch, then final delivery with the full manifest