| --- |
| license: cc-by-4.0 |
| language: |
| - as |
| - bn |
| - gu |
| - hi |
| - kn |
| - ml |
| - mr |
| - ne |
| - or |
| - pa |
| - ta |
| - te |
| - ur |
| task_categories: |
| - automatic-speech-recognition |
| - audio-classification |
| tags: |
| - speech |
| - conversational |
| - multilingual |
| - indian-languages |
| - diarization |
| - asr |
| - tts |
| pretty_name: Multilingual Indian Conversational Speech |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: metadata.jsonl |
| --- |
| |
| # Multilingual Indian Conversational Speech |
|
|
| A dataset of **naturalistic, spontaneous two-speaker conversations** across |
| **13 Indian languages**, with segment-level transcripts, speaker profiles, |
| timestamps, and recording metadata. Designed for ASR, TTS, speaker |
| diarization, and conversational speech research. |
|
|
| ## Languages (13) |
|
|
| Assamese, Bengali, Gujarati, Hindi, Kannada, Malayalam, Marathi, Nepali, |
| Odia, Punjabi, Tamil, Telugu, Urdu. |
|
|
| ## Content |
|
|
| Conversations resemble real-world interactions across multiple domains: |
| Technology / customer support, Financial services, Healthcare, Food & |
| delivery, and Retail & commerce. Speech is conversational and spontaneous — |
| natural turn-taking, code-switching (English mixed with the local language), |
| interruptions, and expressive prosody. |
|
|
| ## Structure |
|
|
| ``` |
| audio/ full conversation recordings (WAV), one per language |
| metadata.jsonl segment-level annotations referencing the recordings |
| ``` |
|
|
| Each row is one **utterance segment** (mostly 1–20 s) that references its |
| source recording in `audio/` with start/end timestamps. |
|
|
| ## Schema |
|
|
| | Field | Type | Description | |
| |---------------------|--------|----------------------------------------------------------| |
| | `segment_id` | string | Segment identifier within a recording (`SEG-001`). | |
| | `recording_id` | string | Source recording ID (`REC-ASM-HLT-011`). | |
| | `audio_file` | string | Relative path to the full recording in `audio/`. | |
| | `language` | string | Language of the conversation. | |
| | `speaker_id` | string | Speaker label (`SPK_01`, `SPK_02`). | |
| | `speaker_role` | string | Conversational role (Customer, Agent, Pharmacist, ...). | |
| | `speaker_gender` | string | Speaker gender (from speaker profile). | |
| | `speaker_age` | string | Age bracket (e.g. `Adult (18+)`). | |
| | `speaker_region` | string | Speaker region/location. | |
| | `accent_dialect` | string | Accent or dialect description. | |
| | `start_time` | string | Segment start (`HH:MM:SS.mmm`). | |
| | `end_time` | string | Segment end (`HH:MM:SS.mmm`). | |
| | `start_seconds` | float | Segment start in seconds. | |
| | `end_seconds` | float | Segment end in seconds. | |
| | `duration_seconds` | float | Segment duration in seconds. | |
| | `transcript` | string | Verbatim transcript in the native script. | |
| | `domain` | string | Conversation domain. | |
| | `collection_method` | string | How the audio was collected. | |
| | `environment_type` | string | Recording environment description. | |
| | `recording_date` | string | Date of recording. | |
| | `sample_rate` | int | Audio sample rate (Hz). | |
| | `channels` | int | Number of audio channels. | |
| | `bit_depth` | int | Audio bit depth. | |
| | `source_recording` | string | Original recording filename. | |
|
|
| ## Audio |
|
|
| - Uncompressed WAV, mostly 48 kHz / 16-bit (some 44.1 kHz and 24-bit). |
| - One full conversation recording per language; segment rows reference offsets |
| within it, so clips can be extracted on demand from `start_seconds` / |
| `end_seconds`. |
|
|
| ## Notes |
|
|
| - Transcripts include natural English code-switching, common in Indian |
| conversational speech. |
| - Timestamps normalized to a consistent `HH:MM:SS.mmm` format; a few segments |
| with source timestamp inconsistencies have a null duration. |
| - Speaker attributes (role, gender, age, region, accent) come from the |
| per-recording speaker profile block in the source annotations. |
|
|
| ## Extracting a segment clip (example) |
|
|
| ```python |
| import soundfile as sf, json |
| row = json.loads(open("metadata.jsonl").readline()) |
| data, sr = sf.read(row["audio_file"]) |
| clip = data[int(row["start_seconds"]*sr):int(row["end_seconds"]*sr)] |
| sf.write("segment.wav", clip, sr) |
| ``` |
|
|
