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