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| license: cc-by-4.0 | |
| language: | |
| - en | |
| - hi | |
| size_categories: | |
| - n<1K | |
| task_categories: | |
| - text-to-speech | |
| - automatic-speech-recognition | |
| tags: | |
| - tts | |
| - indian-english | |
| - hindi | |
| - emotion | |
| - speech | |
| # Indian English + Hindi TTS Mini Dataset | |
| A small (~60 min) speech corpus assembled for TTS training, sourced from | |
| public YouTube content and transcribed with the Sarvam `saaras:v3` model. | |
| ## Summary | |
| | Field | Value | | |
| |---|---| | |
| | Total duration | ~60 min | | |
| | Indian English (en-IN) | ~30 min | | |
| | Hindi (hi-IN) | ~30 min | | |
| | Audio | mono, 16 kHz, WAV | | |
| | Per-clip duration | ≤ 30 s | | |
| | Emotion tags | Angry, Calm, Excited, Formal, Happy, Instruction, Motivation, Narration, Neutral, News, Sad, Surprised, Whisper | | |
| ## Schema | |
| Each row contains: | |
| - `clip_id` — deterministic id, `{video_id}_{start_sec}_{end_sec}` | |
| - `audio` — 16 kHz mono WAV (HuggingFace `Audio` feature) | |
| - `transcription` — Sarvam `saaras:v3` transcript, lightly normalized | |
| - `language` — `en-IN` or `hi-IN` | |
| - `emotion` — one of the categories above | |
| - `speaker_id` — set to source `video_id` (one speaker per source video) | |
| - `duration_sec`, `start_sec`, `end_sec` — integers, seconds | |
| - `video_id`, `source_url` — YouTube provenance | |
| ## Notes & curation | |
| - Clips longer than 30 s in the source spec were split into back-to-back | |
| ≤30 s pieces so they fit Sarvam's sync ASR limit. | |
| - Transcripts come from Sarvam `saaras:v3`; every clip was then reviewed | |
| manually, with multiple iterative passes to correct ASR errors, | |
| normalize spelling, and tighten emotion tags. | |
| - A separate diarization model was **not** used. Each source URL/timestamp | |
| was hand-picked to contain a single speaker, and the manual review | |
| pass listened end-to-end to every clip and re-cut or replaced any | |
| that drifted into multi-speaker territory. | |
| - `speaker_id` is set to the YouTube `video_id` — each source video has | |
| exactly one speaker by construction. | |
| - Emotion tags come from the curator's labelling of each source clip, | |
| refined during the review passes. | |
| ## License | |
| Audio is sourced from YouTube; rights remain with their original creators. | |
| Transcriptions and metadata are released under CC-BY-4.0. Please consult | |
| the original videos for redistribution constraints. | |