---
dataset_info:
  features:
  - name: client_id
    dtype: string
  - name: path
    dtype: string
  - name: sentence_id
    dtype: string
  - name: sentence
    dtype: string
  - name: up_votes
    dtype: int64
  - name: down_votes
    dtype: int64
  - name: age
    dtype: string
  - name: gender
    dtype: string
  - name: accents
    dtype: string
  - name: variant
    dtype: float64
  - name: locale
    dtype: string
  - name: segment
    dtype: float64
  - name: audio
    dtype:
      audio:
        sampling_rate: 16000
  splits:
  - name: train
    num_bytes: 803679362.289
    num_examples: 29789
  - name: validation
    num_bytes: 369560771.408
    num_examples: 10676
  - name: test
    num_bytes: 391035493.648
    num_examples: 10676
  download_size: 1389414072
  dataset_size: 1564275627.345
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
task_categories:
- automatic-speech-recognition
language:
- fa
tags:
- common_voice
- common_voice_22_0
- asr
- automatic_speech_recognition
- persian
- farsi
- persian_language
pretty_name: Common Voice 22.0
---



# Common Voice 22.0 - Persian (fa)

This is an unofficial filtered Persian (Farsi) version of the latest Common Voice dataset version 22.0, obtained from the official Mozilla Common Voice platform at https://commonvoice.mozilla.org/en/datasets. It contains carefully curated and fully validated audio samples aimed at providing a clean and reliable resource for speech processing in Persian. As with the previous version, this dataset is not an official Mozilla release but a community-prepared subset designed to improve the dataset's applicability and quality.

---

## 📊 Dataset Statistics

### 🔹 Train Set (`train`)
| Metric                     | Value                     |
|----------------------------|---------------------------|
| Number of samples          | 29,789                    |
| Total duration             | 31.56 hours (113617.07 seconds) |
| Average sample duration    | 3.81 seconds              |

### 🔹 Validation Set (`validation`)
| Metric                     | Value                     |
|----------------------------|---------------------------|
| Number of samples          | 10,676                    |
| Total duration             | 12.63 hours (45459.50 seconds) |
| Average sample duration    | 4.26 seconds              |

### 🔹 Test Set (`test`)
| Metric                     | Value                     |
|----------------------------|---------------------------|
| Number of samples          | 10,676                    |
| Total duration             | 14.65 hours (52738.05 seconds) |
| Average sample duration    | 4.94 seconds              |

---
### 📈 Overall Statistics
| Metric                     | Value                     |
|----------------------------|---------------------------|
| Number of splits           | 3                         |
| Total number of samples    | 51,141                  |
| Total duration             | 58.84 hours (211814.62 seconds) |
| Average sample duration    | 4.14 seconds              |

---

## 🧪 Usage

```python
from datasets import load_dataset, Audio

dataset = load_dataset("aliyzd95/common_voice_22_0_fa", split="train")
dataset = dataset.cast_column("audio", Audio(sampling_rate=16000))
print(dataset[0]['audio'])
```

---

## 📜 Licensing Information

**Public Domain, CC-0**

---

## 📚 Citation

```bibtex
@inproceedings{commonvoice:2020,
  author    = {Ardila, R. and Branson, M. and Davis, K. and Henretty, M. and Kohler, M. and Meyer, J. and Morais, R. and Saunders, L. and Tyers, F. M. and Weber, G.},
  title     = {Common Voice: A Massively-Multilingual Speech Corpus},
  booktitle = {Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)},
  pages     = {4211--4215},
  year      = {2020}
}
```
---