--- pretty_name: "Tamil call-centre conversations, consumer surveys" language: - ta language_details: ta-IN license: other license_name: lokah-custom license_link: https://kenpathlabs.com/lokah/licensing task_categories: - automatic-speech-recognition size_categories: - n<1K tags: - Tamil speech dataset - conversational speech - call centre audio - speech recognition training data - code-switching - tam --- # Tamil call-centre conversations, consumer surveys > Call-centre conversations in Tamil, consumer surveys, recorded on one channel with speakers labelled. 99 hours. Transcripts are time-aligned and written in Tamil script, with English words kept as spoken. `LK-SP-TAM-002` · [Get a quote](https://kenpathlabs.com/lokah/datasets/tamil-call-centre-customer-service#contact) · [Record as JSON](https://kenpathlabs.com/api/lokah/datasets/tamil-call-centre-customer-service) · [Croissant](https://kenpathlabs.com/lokah/datasets/tamil-call-centre-customer-service/croissant.json) Call-centre conversations in Tamil, consumer surveys, recorded on one channel with speakers labelled. 99 hours. Transcripts are time-aligned and written in Tamil 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 39% of transcript words are English written in Latin script, 9% of the time is silence, and there are 452 turns. 11 distinct voices in the sample (6 female, 5 male). Every recording has a complete, segment-level transcript. Personal data: redacted. Licence: custom, quoted per use. ## Specification | Field | Value | Note | | --- | --- | --- | | id | LK-SP-TAM-002 | | | type | speech · conversational · call centre | | | language | தமிழ் · Tamil · ta-IN | | | hours | 99 h | | | channels | One channel, speakers labelled in the transcript | | | files | 715 files · 715 conversations | counted across the full set | | layouts | 715 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 | 22.9 dB median | across the full set | | release | v1.0 | | | transcript | time-aligned by segment · Tamil script · delivered as JSON | | | speakers | 883 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. 22.9 dB median SNR across the full set, wideband (47 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 | yes | Agent and customer turns in a real support flow. | | Speaker diarisation | yes | Speaker-attributed segments across full conversations. | | Text to speech | no | 22.9 dB median SNR across the full set, wideband (47 dB in the sample conversations): too much background for a voice model. | ## Conversation profile Measured from 6 full conversations (25 minutes, 452 turns, 2800 words). | Measure | Value | | --- | --- | | Talk time, speaker 1 / speaker 2 | 58% / 42% | | Silence | 9% | | Overlapping speech | 0% | | English words, written in Latin script | 39% | | Speaking rate | 124.7 words a minute | One mixed channel: segment edges were placed by an annotator, so turn timing is approximate and overlap is an event label. ## 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) | 47 dB (38.9 to 97.9) | clean | | Noise floor | -71 dBFS | | | Effective bandwidth | 7.9 kHz | wideband (8 kHz) across the full set | | Clipping | 0.000% of samples | | | DNSMOS P.835 (1 to 5) | background 3.45, speech 3.03, overall 2.54 | listener-rated quality, estimated | ## Samples 4 public excerpts, 40.965 seconds each, from different conversations in the dataset. - Sample 1, Call-centre conversation, from a 4-minute conversation (Speaker 1: male; Speaker 2: female): [audio](https://kenpathlabs.com/lokah-samples/tamil-call-centre-customer-service--1.m4a) · [segments](https://kenpathlabs.com/lokah-samples/tamil-call-centre-customer-service--1.segments.json) - Sample 2, Call-centre conversation, from a 4-minute conversation (Speaker 1: female; Speaker 2: male): [audio](https://kenpathlabs.com/lokah-samples/tamil-call-centre-customer-service--2.m4a) · [segments](https://kenpathlabs.com/lokah-samples/tamil-call-centre-customer-service--2.segments.json) - Sample 3, Call-centre conversation, from a 4-minute conversation (Speaker 1: female; Speaker 2: male): [audio](https://kenpathlabs.com/lokah-samples/tamil-call-centre-customer-service--3.m4a) · [segments](https://kenpathlabs.com/lokah-samples/tamil-call-centre-customer-service--3.segments.json) - Sample 4, Call-centre conversation, from a 4-minute conversation (Speaker 1: male; Speaker 2: female): [audio](https://kenpathlabs.com/lokah-samples/tamil-call-centre-customer-service--4.m4a) · [segments](https://kenpathlabs.com/lokah-samples/tamil-call-centre-customer-service--4.segments.json) ### Sample 1 transcript Call-centre conversation, starting at 1:50. Audio sha256 `d57a33380e57b07eae562e0c3244a2ab5930ff81266407ad582dbd02933dfb8a`. | Start | Speaker | Text | | --- | --- | --- | | 0:00 | Speaker 1 | hair shining க்கு? | | 0:01 | Speaker 2 | [filler] five | | 0:02 | Speaker 1 | hair அ dry ஆகாம வேச்சிகிரதுக்கு | | 0:04 | Speaker 2 | five தான் | | 0:06 | Speaker 1 | conditioning effect க்கு | | 0:07 | Speaker 2 | five | | 0:09 | Speaker 1 | powder ஓட துகள் hair ல தங்காம easy remove ஆகுறதுக்கு | | 0:11 | Speaker 2 | five | | 0:13 | Speaker 1 | OK [unintelligible] ஆ release பண்றதுக்கு | | 0:16 | Speaker 2 | [filler] five தாங்க | | 0:18 | Speaker 1 | நொறையோட அளவுக்கு | | 0:19 | Speaker 2 | அதுவும் five தான் | | 0:21 | Speaker 1 | hair soft ஆ smooth ஆ இருக்குறதுக்கு | | 0:23 | Speaker 2 | அதுவும் five தான் | | 0:25 | Speaker 1 | dandruff reduce ஆகுறதுக்கு | | 0:26 | Speaker 2 | five | | 0:27 | Speaker 1 | white flex லாம் remove ஆகுறதுக்கு, | | 0:30 | Speaker 2 | [filler] five | | 0:31 | Speaker 1 | hair fall control பண்ணுறதுக்கு | | 0:33 | Speaker 2 | [filler] five | | 0:34 | Speaker 1 | itching reduce ஆகுறதுக்கு | | 0:36 | Speaker 2 | [filler] five தான் | | 0:37 | Speaker 1 | fresh ஆ இருக்குற மாதிரி feel குடுக்குறதுக்கு | | 0:39 | Speaker 2 | five தான் | ## Licence Licence: custom, quoted per use (training, evaluation or both; internal or commercial; exclusive or not). Delivered in the layout your training code reads: https://kenpathlabs.com/lokah/formats. --- Machine-readable: [llms.txt](https://kenpathlabs.com/llms.txt) · [JSON API](https://kenpathlabs.com/api/lokah/datasets) · [OpenAPI](https://kenpathlabs.com/lokah/openapi.json) · [MCP](https://kenpathlabs.com/api/lokah/mcp) · [for agents](https://kenpathlabs.com/lokah/for-agents)