--- pretty_name: "Marathi call-centre conversations, banking and insurance" language: - mr language_details: mr-IN license: other license_name: lokah-custom license_link: https://kenpathlabs.com/lokah/licensing task_categories: - automatic-speech-recognition size_categories: - n<1K tags: - Marathi speech dataset - conversational speech - call centre audio - speech recognition training data - code-switching - mar --- # Marathi call-centre conversations, banking and insurance > Call-centre conversations in Marathi, banking and insurance, recorded on one channel with speakers labelled. 4 hours. Transcripts are time-aligned and written in Devanagari script, with English words kept as spoken. `LK-SP-MAR-002` · [Get a quote](https://kenpathlabs.com/lokah/datasets/marathi-call-centre-banking-and-insurance#contact) · [Record as JSON](https://kenpathlabs.com/api/lokah/datasets/marathi-call-centre-banking-and-insurance) · [Croissant](https://kenpathlabs.com/lokah/datasets/marathi-call-centre-banking-and-insurance/croissant.json) Call-centre conversations in Marathi, banking and insurance, recorded on one channel with speakers labelled. 4 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 0% of transcript words are English written in Latin script, 10% of the time is silence, and there are 309 turns. 8 distinct voices in the sample (4 female, 3 male, 1 unknown). Every recording has a complete, segment-level transcript. Personal data: redacted. Licence: custom, quoted per use. ## Specification | Field | Value | Note | | --- | --- | --- | | id | LK-SP-MAR-002 | | | type | speech · conversational · call centre | | | language | मराठी · Marathi · mr-IN | | | hours | 4 h | | | channels | One channel, speakers labelled in the transcript | | | files | 17 files · 17 conversations | counted across the full set | | layouts | 17 mono conversation | counted across the full set | | audio | FLAC · 16 kHz · 16-bit | measured across the full set | | bandwidth | telephone (4 kHz) | no telephone-band files | | snr | 35.5 dB median | across the full set | | release | v1.0 | | | transcript | time-aligned by segment · Devanagari script · delivered as JSON | | | speakers | 18 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 | Call-centre recordings | | | 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. 35.5 dB median SNR across the full set (43.7 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 | 35.5 dB median SNR across the full set (43.7 dB in the sample conversations): too much background for a voice model. | ## Conversation profile Measured from 6 full conversations (25 minutes, 309 turns, 3077 words). | Measure | Value | | --- | --- | | Talk time, speaker 1 / speaker 2 | 42% / 58% | | Silence | 10% | | Overlapping speech | 4% | | English words, written in Latin script | 0% | | Speaking rate | 139.9 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) | 43.7 dB (39.2 to 50.6) | clean | | Noise floor | -72.5 dBFS | | | Effective bandwidth | 4.7 kHz | telephone (4 kHz) across the full set | | Clipping | 0.000% of samples | | | DNSMOS P.835 (1 to 5) | background 3.46, speech 3.23, overall 2.67 | listener-rated quality, estimated | ## Samples 4 public excerpts, 41.534 seconds each, from different conversations in the dataset. - Sample 1, Call-centre conversation, from a 4-minute conversation (Speaker 1: gender unknown; Speaker 2: male): [audio](https://kenpathlabs.com/lokah-samples/marathi-call-centre-banking-and-insurance--1.m4a) · [segments](https://kenpathlabs.com/lokah-samples/marathi-call-centre-banking-and-insurance--1.segments.json) - Sample 2, Call-centre conversation, from a 4-minute conversation (Speaker 1: female; Speaker 2: female): [audio](https://kenpathlabs.com/lokah-samples/marathi-call-centre-banking-and-insurance--2.m4a) · [segments](https://kenpathlabs.com/lokah-samples/marathi-call-centre-banking-and-insurance--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/marathi-call-centre-banking-and-insurance--3.m4a) · [segments](https://kenpathlabs.com/lokah-samples/marathi-call-centre-banking-and-insurance--3.segments.json) - Sample 4, Call-centre conversation, from a 4-minute conversation (Speaker 1: gender unknown; Speaker 2: female): [audio](https://kenpathlabs.com/lokah-samples/marathi-call-centre-banking-and-insurance--4.m4a) · [segments](https://kenpathlabs.com/lokah-samples/marathi-call-centre-banking-and-insurance--4.segments.json) ### Sample 1 transcript Call-centre conversation, starting at 0:22. Audio sha256 `ed0f74cff2a232b8014d82089278ef6d4a10f90aa6c75727cc3941414ea04dae`. | Start | Speaker | Text | | --- | --- | --- | | 0:00 | Speaker 2 | हा कुठून विश्वास बँक का? | | 0:02 | Speaker 1 | हो सर | | 0:04 | Speaker 2 | बरं बरं बोला सर. | | 0:05 | Speaker 1 | सर तुम्हाला क्रेडिट कार्ड हवं आहे का? | | 0:09 | Speaker 2 | हम्म | | 0:10 | Speaker 1 | क्रेडिट कार्ड हवाय का सर तुम्हाला? | | 0:13 | Speaker 2 | आ हा मी केली होती रिक्वेस्ट बोला काय म्हणताय. | | 0:17 | Speaker 1 | हो सर मी तुम्हाला आमच्याकडे क्रेडीट कार्डचा काही ऑफरसये तुम्हाला सांगतो सर मी | | 0:23 | Speaker 1 | बट तरी तुमचे काही माहिती लागेल सर तुम्हाला विचारू शकतो का? | | 0:27 | Speaker 2 | हा सर ते मिनिट ह्ह | | 0:29 | Speaker 1 | हॅलो सर | | 0:30 | Speaker 2 | [unclear] तुम्ही विश्वास बँकेतून बोलतायत नाव पुन्हा एकदा सांगा [unclear] | | 0:34 | Speaker 1 | साहिल भालेराव सर साहिल भालेराव. | | 0:38 | Speaker 2 | साहिल भालेराव बर | | 0:40 | Speaker 1 | हो सर | ## Licence Licence: custom, quoted per use (training, evaluation or both; internal or commercial; exclusive or not). 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