---
language:
- fa
task_categories:
- automatic-speech-recognition
- text-to-speech
- text-to-speech
dataset_info:
  features:
  - name: audio
    dtype: audio
  - name: transcription
    dtype: string
  - name: Length (seconds)
    dtype: int64
  splits:
  - name: train
    num_bytes: 368910411.993
    num_examples: 2101
  download_size: 365903240
  dataset_size: 368910411.993
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
tags:
- Benchmark
- Speech
- STT
- ASR
---



This dataset consists of 3 hours of 16kHz audio collected from diverse environments to better represent real-world scenarios. The recordings were sourced from audiobooks, YouTube, and other public sources, ensuring a wide variety of speech styles and acoustic conditions.

One key advantage of this dataset is that it was collected from recent sources within the last few months, ensuring no overlap with training data and fairness for evaluating other STT models.

To enable a robust and fair comparison of models, the dataset has been carefully normalized: extra characters and inconsistencies in Persian text have been removed, and orthographic variations have been standardized.

<p align="center">
    <img src="assets/plot.png" alt="Evaluation of different models on the dataset" />
</p>

For a detailed explanation of the normalization process, please refer to our [GitHub page](https://github.com/c1tech-group/Persian-ASR-Leaderboard).