|
|
--- |
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dataset_info: |
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features: |
|
|
- name: audio |
|
|
dtype: audio |
|
|
- name: text |
|
|
dtype: string |
|
|
- name: lang |
|
|
dtype: string |
|
|
- name: emotion |
|
|
dtype: string |
|
|
- name: duration |
|
|
dtype: float64 |
|
|
- name: utt_id |
|
|
dtype: string |
|
|
- name: speaker_id |
|
|
dtype: string |
|
|
- name: source |
|
|
dtype: string |
|
|
- name: snr_db |
|
|
dtype: float64 |
|
|
- name: silence_ratio |
|
|
dtype: float64 |
|
|
- name: clipping_ratio |
|
|
dtype: float64 |
|
|
- name: domain |
|
|
dtype: string |
|
|
configs: |
|
|
- config_name: assamese |
|
|
data_files: |
|
|
- split: train |
|
|
path: assamese/train-*.parquet |
|
|
- split: validation |
|
|
path: assamese/validation-*.parquet |
|
|
- config_name: bengali |
|
|
data_files: |
|
|
- split: train |
|
|
path: bengali/train-*.parquet |
|
|
- split: validation |
|
|
path: bengali/validation-*.parquet |
|
|
- config_name: english |
|
|
data_files: |
|
|
- split: train |
|
|
path: english/train-*.parquet |
|
|
- split: validation |
|
|
path: english/validation-*.parquet |
|
|
- config_name: gujarati |
|
|
data_files: |
|
|
- split: train |
|
|
path: gujarati/train-*.parquet |
|
|
- split: validation |
|
|
path: gujarati/validation-*.parquet |
|
|
- config_name: hindi |
|
|
data_files: |
|
|
- split: train |
|
|
path: hindi/train-*.parquet |
|
|
- split: validation |
|
|
path: hindi/validation-*.parquet |
|
|
- config_name: kannada |
|
|
data_files: |
|
|
- split: train |
|
|
path: kannada/train-*.parquet |
|
|
- split: validation |
|
|
path: kannada/validation-*.parquet |
|
|
- config_name: malayalam |
|
|
data_files: |
|
|
- split: train |
|
|
path: malayalam/train-*.parquet |
|
|
- split: validation |
|
|
path: malayalam/validation-*.parquet |
|
|
- config_name: marathi |
|
|
data_files: |
|
|
- split: train |
|
|
path: marathi/train-*.parquet |
|
|
- split: validation |
|
|
path: marathi/validation-*.parquet |
|
|
- config_name: nepali |
|
|
data_files: |
|
|
- split: train |
|
|
path: nepali/train-*.parquet |
|
|
- split: validation |
|
|
path: nepali/validation-*.parquet |
|
|
- config_name: odia |
|
|
data_files: |
|
|
- split: train |
|
|
path: odia/train-*.parquet |
|
|
- split: validation |
|
|
path: odia/validation-*.parquet |
|
|
- config_name: punjabi |
|
|
data_files: |
|
|
- split: train |
|
|
path: punjabi/train-*.parquet |
|
|
- split: validation |
|
|
path: punjabi/validation-*.parquet |
|
|
- config_name: tamil |
|
|
data_files: |
|
|
- split: train |
|
|
path: tamil/train-*.parquet |
|
|
- split: validation |
|
|
path: tamil/validation-*.parquet |
|
|
- config_name: telugu |
|
|
data_files: |
|
|
- split: train |
|
|
path: telugu/train-*.parquet |
|
|
- split: validation |
|
|
path: telugu/validation-*.parquet |
|
|
--- |
|
|
|
|
|
# Indic Multilingual TTS Dataset |
|
|
|
|
|
Large-scale multilingual text-to-speech dataset covering 13 Indian languages with 453,823 utterances. |
|
|
Audio is embedded in Parquet files and playable directly in the dataset viewer. |
|
|
|
|
|
## Languages |
|
|
|
|
|
| Language | Code | Config | Train | Validation | |
|
|
|----------|------|--------|------:|-----------:| |
|
|
| Assamese | `as` | `assamese` | 52,251 | 500 | |
|
|
| Bengali | `bn` | `bengali` | 44,637 | 500 | |
|
|
| English | `en` | `english` | 12,209 | 500 | |
|
|
| Gujarati | `gu` | `gujarati` | 16,157 | 500 | |
|
|
| Hindi | `hi` | `hindi` | 24,211 | 500 | |
|
|
| Kannada | `kn` | `kannada` | 32,263 | 500 | |
|
|
| Malayalam | `ml` | `malayalam` | 44,381 | 499 | |
|
|
| Marathi | `mr` | `marathi` | 28,161 | 499 | |
|
|
| Nepali | `ne` | `nepali` | 41,320 | 500 | |
|
|
| Odia | `or` | `odia` | 26,468 | 500 | |
|
|
| Punjabi | `pa` | `punjabi` | 28,598 | 500 | |
|
|
| Tamil | `ta` | `tamil` | 53,075 | 499 | |
|
|
| Telugu | `te` | `telugu` | 43,595 | 500 | |
|
|
| **Total** | | | **447,326** | **6,497** | |
|
|
|
|
|
## Usage |
|
|
|
|
|
```python |
|
|
from datasets import load_dataset |
|
|
|
|
|
# Load a specific language |
|
|
ds = load_dataset("PalakEngineerMaster/Validated_data_TTS", "hindi") |
|
|
|
|
|
# Access audio |
|
|
sample = ds["train"][0] |
|
|
print(sample["audio"]) # {"array": ndarray, "sampling_rate": 16000} |
|
|
print(sample["text"]) # transcription |
|
|
``` |
|
|
|
|
|
## Columns |
|
|
|
|
|
- `audio`: Audio waveform (WAV, 16kHz mono) — playable in viewer |
|
|
- `text`: Transcription |
|
|
- `lang`: Language code |
|
|
- `emotion`: Emotion label |
|
|
- `duration`: Duration in seconds |
|
|
- `utt_id` / `speaker_id`: Utterance and speaker identifiers |
|
|
- `source`: Data source (rasa, indicvoices_r, indictts) |
|
|
- `snr_db`: Signal-to-noise ratio (dB) |
|
|
- `silence_ratio` / `clipping_ratio`: Audio quality metrics |
|
|
- `domain`: Domain category |
|
|
|
|
|
## Sources |
|
|
|
|
|
- [IndicVoices-R](https://ai4bharat.iitm.ac.in/indicvoices_r) |
|
|
- [RASA](https://ai4bharat.iitm.ac.in/rasa) |
|
|
- [IndicTTS](https://www.iitm.ac.in/donlab/tts/database.php) |
|
|
|
