--- pretty_name: "Hindi general conversation" language: - hi language_details: hi-IN license: other license_name: lokah-custom license_link: https://kenpathlabs.com/lokah/licensing task_categories: - automatic-speech-recognition size_categories: - n<1K tags: - Hindi speech dataset - conversational speech - spontaneous conversation - speech recognition training data - code-switching - hin --- # Hindi general conversation > Two-speaker general conversation in Hindi, recorded on one channel with speakers labelled. 81 hours. Transcripts are time-aligned and written in Devanagari script, with English words kept as spoken. `LK-SP-HIN-002` · [Get a quote](https://kenpathlabs.com/lokah/datasets/hindi-general-conversation#contact) · [Record as JSON](https://kenpathlabs.com/api/lokah/datasets/hindi-general-conversation) · [Croissant](https://kenpathlabs.com/lokah/datasets/hindi-general-conversation/croissant.json) Two-speaker general conversation in Hindi, recorded on one channel with speakers labelled. 81 hours. Transcripts are time-aligned and written in Devanagari script, with English words kept as spoken. Measured from 6 sample conversations (25 minutes): 16 kHz, 16-bit PCM WAV, one mono file per conversation. Across them 14% of transcript words are English written in Latin script, 17% of the time is silence, and there are 359 turns. 11 distinct voices in the sample (4 male, 7 female). Every recording has a complete, segment-level transcript. Personal data: redacted. Licence: custom, quoted per use. ## Specification | Field | Value | Note | | --- | --- | --- | | id | LK-SP-HIN-002 | | | type | speech · conversational · general | | | language | हिन्दी · Hindi · hi-IN | | | hours | 81 h | | | channels | One channel, speakers labelled in the transcript | | | files | 259 files · 259 conversations | counted across the full set | | layouts | 259 mono conversation | counted across the full set | | audio | FLAC · 16 kHz · 16-bit | measured across the full set | | bandwidth | wideband (8 kHz) | no telephone-band files | | snr | 36.8 dB median | across the full set | | release | v1.0 | | | transcript | time-aligned by segment · Devanagari script · delivered as JSON | | | speakers | 177 across the full set · id and gender per speaker | | | pii | Numbers of 4 or more digits, digit strings spoken as words, and email addresses are masked as [pii] in text and replaced by a tone in audio. First names are not masked. | | | source | Recorded for the dataset | | | review | Every recording has a complete, segment-level transcript | | | personal data | Redacted | | | licence | Custom | quoted per use | ## What it is good for | Task | Fit | Why | | --- | --- | --- | | Speech recognition | yes | Time-aligned transcripts in native script, English kept as spoken. 36.8 dB median SNR across the full set, wideband (53 dB in the sample conversations). | | Full-duplex speech to speech | partly | One mixed channel. Turns are labelled, but overlapping speech cannot be separated, which these models need. | | Turn-taking and endpointing | partly | Turn boundaries come from the transcript, so gaps are approximate and overlap is marked, not separated. | | Voice agents for support | partly | Open conversation, not a support flow. Useful for language and prosody, not for task structure. | | Speaker diarisation | yes | Speaker-attributed segments across full conversations. | | Text to speech | partly | 36.8 dB median SNR across the full set, wideband (53 dB in the sample conversations): clean and wideband enough for conversational prosody data, though not a studio voice. | ## Conversation profile Measured from 6 full conversations (25 minutes, 359 turns, 3631 words). | Measure | Value | | --- | --- | | Talk time, speaker 1 / speaker 2 | 48% / 52% | | Silence | 17% | | Overlapping speech | 1% | | English words, written in Latin script | 14% | | Speaking rate | 176.8 words a minute | One mixed channel: segment edges were placed by an annotator, so turn timing is approximate and overlap is an event label (1 in this conversation). ## Audio quality Frame RMS at 20 ms on the channels mixed to mono. Noise floor is the 10th percentile, speech level the 90th; SNR is their difference. Bandwidth is the highest frequency at which speech still rises 6 dB above the recording's own noise spectrum. | Measure | Value | Reading | | --- | --- | --- | | Speech above noise floor (SNR) | 53 dB (36.2 to 107.2) | some background | | Noise floor | -75.7 dBFS | | | Effective bandwidth | 8.0 kHz | wideband (8 kHz) across the full set | | Clipping | 0.015% of samples | | | DNSMOS P.835 (1 to 5) | background 3.75, speech 3.29, overall 2.88 | listener-rated quality, estimated | ## Samples 4 public excerpts, 44.161 seconds each, from different conversations in the dataset. - Sample 1, Open conversation, from a 4-minute conversation (Speaker 1: male; Speaker 2: male): [audio](https://kenpathlabs.com/lokah-samples/hindi-general-conversation--1.m4a) · [segments](https://kenpathlabs.com/lokah-samples/hindi-general-conversation--1.segments.json) - Sample 2, Open conversation, from a 4-minute conversation (Speaker 1: female; Speaker 2: female): [audio](https://kenpathlabs.com/lokah-samples/hindi-general-conversation--2.m4a) · [segments](https://kenpathlabs.com/lokah-samples/hindi-general-conversation--2.segments.json) - Sample 3, Open conversation, from a 4-minute conversation (Speaker 1: male; Speaker 2: male): [audio](https://kenpathlabs.com/lokah-samples/hindi-general-conversation--3.m4a) · [segments](https://kenpathlabs.com/lokah-samples/hindi-general-conversation--3.segments.json) - Sample 4, Open conversation, from a 4-minute conversation (Speaker 1: female; Speaker 2: female): [audio](https://kenpathlabs.com/lokah-samples/hindi-general-conversation--4.m4a) · [segments](https://kenpathlabs.com/lokah-samples/hindi-general-conversation--4.segments.json) ### Sample 1 transcript Open conversation, starting at 0:20. Audio sha256 `0909ab3c1e2cf776a2610409d611e09665f7ab34304210efbf3aa6b05b5b8542`. | Start | Speaker | Text | | --- | --- | --- | | 0:00 | Speaker 2 | हम्म शुरू हो गया कल से शुरू हुआ है। | | 0:02 | Speaker 1 | ओह I C C ना? | | 0:04 | Speaker 2 | हम्म | | 0:05 | Speaker 1 | अच्छा ठीक है। | | 0:09 | Speaker 2 | क्या कल तो opening था ना। | | 0:11 | Speaker 1 | हम्म | | 0:12 | Speaker 2 | england और new zeeland का बीच में था। | | 0:14 | Speaker 1 | हाँ हाँ। | | 0:16 | Speaker 2 | नया एक stadium बना है इंडिया में नरेंद्र मोदी stadium ना। | | 0:19 | Speaker 1 | हाँ हाँ हाँ। | | 0:19 | Speaker 2 | हैदराबाद में। | | 0:20 | Speaker 1 | ह्म्म्म | | 0:21 | Speaker 2 | [filler] वो हमें वो था इनके साथ [unintelligible] [silence] क्या था ये उसको क्या बोलते हो। | | 0:27 | Speaker 1 | [filler] fans लोग जो? | | 0:29 | Speaker 2 | fans लोग [overlap] जो | | 0:29 | Speaker 1 | [overlap] attendance | | 0:30 | Speaker 1 | नहीं था ना ज्यादा। | | 0:31 | Speaker 2 | attendance नहीं था forty three thousand कुछ ही था। | | 0:33 | Speaker 1 | [filler] वाह forty three thousand मामूली है लेकिन बड़ा है नरेंद्र मोदी stadium जो? | | 0:37 | Speaker 2 | बहुत बड़ा है उसमें एक लाख से ज्यादा capacity है। | | 0:40 | Speaker 1 | हम्म | | 0:41 | Speaker 2 | तो उसमें इतना कम आया है। | | 0:43 | Speaker 1 | हाँ। | ## Licence Licence: custom, quoted per use (training, evaluation or both; internal or commercial; exclusive or not). 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