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# Dataset Card for PSRB (Persian Speech Recognition Benchmark) - 1-Hour Sample
## Dataset Summary
The Persian Speech Recognition Benchmark (PSRB) is a comprehensive dataset designed to evaluate Persian Automatic Speech Recognition (ASR) systems under diverse real-world conditions.
This 1-hour sample provides a representative subset of the full PSRB corpus, capturing various accents, speech styles, speaker demographics, and acoustic environments.
## Supported Tasks and Leaderboards
- Automatic Speech Recognition (ASR)
## Languages
- Persian (Farsi)
## Dataset Structure
### Data Instances
Each data instance in this sample is structured as:
```json
{
"audio_path": "file1.wav",
"text": "میگم نمیخواین طبق نقشه جلو بریم؟ نقشه رو بیخیال غمت نباشه ما مستر رد پا رو داریم. حس بویایی و شمام اشتباه نمیکنه. همین الان اشتباه کرده.",
"audio_duration": 11.88,
"number_of_speakers": 3,
"gender": "male",
"age": "mix",
"accents": "standard",
"formality": "informal",
"semantic_content": "artistic&literary",
"data_source": "animation",
"acoustic_environment": "noisy",
"spontaneous": 1
}
```
### Data Fields
- **`audio_path`**: Path to the `.wav` audio file.
- **`text`**: Transcription of the audio in Persian.
- **`audio_duration`**: Duration of the audio file in seconds.
- **`number_of_speakers`**: Number of speakers present in the clip.
- **`gender`**: Gender of the speaker(s).
- **`age`**: Age category (e.g., child, teen, adult, senior, or mix).
- **`accents`**: Regional accent of the speaker or "standard."
- **`formality`**: Formality level ("formal" or "informal").
- **`semantic_content`**: Semantic topic or domain of the speech (e.g., artistic&literary, technological, medical).
- **`data_source`**: Source type of the data (e.g., animation, podcast, lecture).
- **`acoustic_environment`**: Recording environment (e.g., clean, noisy).
- **`spontaneous`**: 1 if speech is spontaneous, 0 if scripted.
---
## Dataset Creation
### Curation Rationale
The PSRB dataset was created to address the lack of comprehensive Persian ASR resources, covering linguistic diversity (accents, formality) and acoustic variability (clean, noisy, phone calls).
### Source Data
Data sources include:
- News broadcasts
- Movies and TV shows
- Podcasts
- Lectures
- Audiobooks
- Talk shows
Collected from platforms such as Telewebion, Aparat, YouTube, and Iranseda.
### Annotations
- Transcriptions manually created by expert native Persian speakers.
- Strict two-pass quality control review to ensure consistency and correctness.
- Rich metadata labeling for speaker demographics and speech conditions.
### Personal and Sensitive Information
- All data was anonymized to protect the identity of participants.
- No personally identifiable information (PII) is present in this dataset.
---
## Considerations for Using the Data
### Limitations
- This sample may not capture the full variability of the complete PSRB corpus.
---
## Additional Information
### Licensing Information
This dataset is made available for **research and educational purposes only**.
---
## Citation Information
If you use this dataset in your research, please cite:
```bibtex
@misc{psrb2025,
title={PSRB: A Comprehensive Benchmark for Evaluating Persian Automatic Speech Recognition Systems},
author={Nima Sedghiye and Sara Sadeghi and Reza Khodadadi and Farzin Kashani and Omid Aghdaei and Somayeh Rahimi and Mohammad Sadegh Safari},
year={2025},
publisher={Part AI Research Center},
note={Preprint}
} |