README.md

---
license: cc-by-4.0
language:
- ta
task_categories:
- automatic-speech-recognition
tags:
- audio
- text
- speech
- tamil
- openslr
pretty_name: OpenSLR-65 Tamil Speech Dataset
size_categories:
- 1K<n<10K
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
dataset_info:
  features:
  - name: file_id
    dtype: string
  - name: audio
    dtype: audio
  - name: transcription
    dtype: string
  - name: duration
    dtype: float32
  - name: gender
    dtype: string
  splits:
  - name: train
    num_bytes: 2449492064.0
    num_examples: 4291
  download_size: 1787306633
  dataset_size: 2449492064.0
---

# OpenSLR-65 – Tamil Transcribed Speech

**Source:** [https://www.openslr.org/65/](https://www.openslr.org/65/)

## Dataset Description
- **Homepage:** [OpenSLR SLR65](https://www.openslr.org/65/)

This dataset contains transcribed high-quality audio of Tamil sentences recorded
by volunteers. It is part of the [OpenSLR](https://www.openslr.org) collection of
free speech resources for low-resource languages.

The data was collected via the
[Appen](https://appen.com) (formerly Figure Eight / CrowdFlower) crowdsourcing
platform and is intended for use in training automatic speech recognition (ASR)
and text-to-speech (TTS) systems.

### Data Collection

Volunteers were asked to read Tamil sentences displayed on their screen and
record themselves. Quality control was performed to ensure accurate transcriptions
and clean audio.

### Contents

| Field | Description |
|-------|-------------|
| `file_id` | Anonymized identifier for the audio file |
| `transcription` | Tamil text transcription of the utterance |
| `audio` | WAV audio file (mono) |
| `duration` | Duration of the audio in seconds |
| `gender` | Speaker gender (`male` / `female`) |

## Corpus statistics
| gender | samples | duration (h) |
|--------|---------|------------|
| female | 2 335   |  4.01      |
|   male | 1 956   |  3.07      |
| **total** | **4 291** | **7.08** |

## Usage

### Load the Dataset

```python
from datasets import load_dataset

# Load full dataset
dataset = load_dataset("deepdml/openslr65-tamil")
train_data = dataset["train"]
# train_data = load_dataset("deepdml/openslr65-tamil", split="train")
```

### Inspect a Sample

```python
sample = train_data[0]

print(sample)
# {
#   'file_id':    'tag_09162_01279273055',
#   'audio':      {'array': array([...], dtype=float32)},
#   'transcription': 'அவர்களின் படங்களின் டீஸருக்கு கிடைக்கும் வரவேற்பு அபிரிதமாக உள்ளது',
#   'duration':   5.12,
#   'gender': male,
# }

# Play audio (in a notebook)
import IPython.display as ipd
ipd.Audio(sample["audio"]["array"], rate=sample["audio"]["sampling_rate"])
```

### Filter by Duration

```python
# Keep only utterances between 2 and 15 seconds
filtered = train_data.filter(lambda x: 2.0 <= x["duration"] <= 15.0)
```

## License

[Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/)

## Citation

If you use this dataset, please cite:

```
@inproceedings{he-etal-2020-open,
    title = {{Open-source Multi-speaker Speech Corpora for Building Gujarati, Kannada, Malayalam, Marathi, Tamil and Telugu Speech Synthesis Systems}},
    author = {He, Fei and Chu, Shan-Hui Cathy and Kjartansson, Oddur and Rivera, Clara and Katanova, Anna and Gutkin, Alexander and Demirsahin, Isin and Johny, Cibu and Jansche, Martin and Sarin, Supheakmungkol and Pipatsrisawat, Knot},
    booktitle = {Proceedings of The 12th Language Resources and Evaluation Conference (LREC)},
    month = may,
    year = {2020},
    address = {Marseille, France},
    publisher = {European Language Resources Association (ELRA)},
    pages = {6494--6503},
    url = {https://www.aclweb.org/anthology/2020.lrec-1.800},
    ISBN = "{979-10-95546-34-4},
  }
```

## Additional Information

- **Homepage:** https://www.openslr.org/65/
- **Repository:** https://openslr.org/resources/65/
- **Paper:** N/A
- **Point of Contact:** OpenSLR maintainers