| --- |
| language: |
| - as |
| - bn |
| - en |
| - gu |
| - hi |
| - kn |
| - ml |
| - mr |
| - ne |
| - or |
| - pa |
| - ta |
| - te |
| license: cc-by-4.0 |
| task_categories: |
| - text-to-speech |
| - automatic-speech-recognition |
| size_categories: |
| - 100K<n<1M |
| tags: |
| - indic |
| - multilingual |
| - tts |
| - speech |
| --- |
| |
| # Processed TTS Multilingual Data |
|
|
| Validated and quality-checked multilingual speech datasets for TTS training, covering 12+ Indian languages. |
|
|
| ## Datasets Included |
|
|
| | Subset | Samples | Hours | Description | |
| |---|---|---|---| |
| | `indic_voices_r` | 239,684 | 548.8h | Indic Voices_R — IVR recordings | |
| | `rasa` | 201,509 | 361.2h | RASA — read speech (wiki, conv, book, news) | |
| | `indictts_iitm` | 155,236 | 253.6h | Indic TTS (IIT Madras) — studio TTS recordings at 48kHz | |
| | **Total** | **596,429** | **1,163.6h** | | |
|
|
| ## Languages |
|
|
| Assamese (as), Bengali (bn), English (en), Gujarati (gu), Hindi (hi), Kannada (kn), Malayalam (ml), Marathi (mr), Nepali (ne), Odia (or), Punjabi (pa), Tamil (ta), Telugu (te) |
|
|
| ## Structure |
|
|
| ``` |
| ├── indic_voices_r/ |
| │ ├── metadata.csv |
| │ └── audio/{lang}/*.wav |
| ├── rasa/ |
| │ ├── metadata.csv |
| │ └── audio/{lang}/*.wav |
| └── indictts_iitm/ |
| ├── metadata.csv |
| └── audio/{lang}/*.wav |
| ``` |
|
|
| ## Schema (metadata.csv) |
|
|
| Each subset has a `metadata.csv` with these columns: |
|
|
| | Field | Description | |
| |---|---| |
| | `file_name` | Relative path to audio file (e.g., `audio/bn/file.wav`) | |
| | `text` | Transcript text | |
| | `lang` | ISO 639-1 language code | |
| | `speaker_id` | Speaker identifier | |
| | `duration` | Audio duration in seconds | |
| | `source` | Original data source | |
| | `emotion` | Emotion label | |
| | `domain` | Text domain (wiki, conv, book, news, etc.) | |
| | `snr_db` | Signal-to-noise ratio in dB | |
| | `silence_ratio` | Fraction of silent frames | |
| | `clipping_ratio` | Fraction of clipped samples | |
|
|
| ## Quality Checks Applied |
|
|
| All data has been validated through a 4-check pipeline: |
| 1. **SNR + Silence + Duration** — reject low SNR (<10dB), excess silence (>35%), out-of-range duration (<1.5s or >30s), clipping (>1%) |
| 2. **Speaking Rate** — reject abnormal speaking rates (<2 or >25 chars/sec) |
| 3. **Text Normalization** — Unicode NFC normalization applied |
| 4. **Audio Corruption** — reject empty, all-zeros, NaN/Inf, DC offset >0.1 |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| |
| # Load a specific subset |
| ds = load_dataset( |
| "PalakEngineerMaster/Processed_TTS_Multilingual_Data", |
| data_dir="rasa", |
| split="train", |
| ) |
| |
| # Access a sample |
| sample = ds[0] |
| print(sample["text"]) |
| # audio is at sample["file_name"] |
| ``` |
|
|
| ## Audio Format |
|
|
| - Format: WAV |
| - Sample rate: 16kHz (Indic Voices_R, RASA) / 48kHz (Indic TTS IIT M) |
| - Channels: mono |
| |
