YAML Metadata Warning: The task_ids "speech-recognition" is not in the official list: acceptability-classification, entity-linking-classification, fact-checking, intent-classification, language-identification, multi-class-classification, multi-label-classification, multi-input-text-classification, natural-language-inference, semantic-similarity-classification, sentiment-classification, topic-classification, semantic-similarity-scoring, sentiment-scoring, sentiment-analysis, hate-speech-detection, text-scoring, named-entity-recognition, part-of-speech, parsing, lemmatization, word-sense-disambiguation, coreference-resolution, extractive-qa, open-domain-qa, closed-domain-qa, news-articles-summarization, news-articles-headline-generation, dialogue-modeling, dialogue-generation, conversational, language-modeling, text-simplification, explanation-generation, abstractive-qa, open-domain-abstractive-qa, closed-domain-qa, open-book-qa, closed-book-qa, slot-filling, masked-language-modeling, keyword-spotting, speaker-identification, audio-intent-classification, audio-emotion-recognition, audio-language-identification, multi-label-image-classification, multi-class-image-classification, face-detection, vehicle-detection, instance-segmentation, semantic-segmentation, panoptic-segmentation, image-captioning, image-inpainting, image-colorization, super-resolution, grasping, task-planning, tabular-multi-class-classification, tabular-multi-label-classification, tabular-single-column-regression, rdf-to-text, multiple-choice-qa, multiple-choice-coreference-resolution, document-retrieval, utterance-retrieval, entity-linking-retrieval, fact-checking-retrieval, univariate-time-series-forecasting, multivariate-time-series-forecasting, visual-question-answering, document-question-answering, pose-estimation

ParsVoice - Persian Speech Recognition Dataset

Dataset Description

ParsVoice is a high-quality Persian (Farsi) speech recognition dataset created from audiobooks. The dataset features clean, professionally narrated speech with accurate transcriptions.

Dataset Statistics

Total Samples: 2,624
Total Books: 10
Total Narrators: 5
Language: Persian (Farsi)
Sampling Rate: 16 kHz
Audio Format: WAV

Features

audio: High-quality 16kHz audio segments
transcription: Raw transcription text
transcription_with_punctuation: Transcription with restored punctuation
speaker_id: Encoded speaker/narrator identifier
book_id: Encoded book identifier
is_complete: Whether the segment contains a complete sentence
duration_seconds: Length of audio segment
snr_db: Signal-to-noise ratio
quality_score: Overall quality score (0-100)
segment_type: Type of segment processing applied
was_smart_trimmed: Whether smart trimming was applied

Quality Assurance

All segments pass quality filters for SNR, background music detection, and distortion
Smart trimming applied to remove excess silence while preserving speech content
Only high-quality segments with clear transcriptions included

Privacy

Book titles and narrator names are encoded for privacy
Original content identification is not possible from the dataset

Usage

from datasets import load_dataset

dataset = load_dataset("MohammadJRanjbar/ParsVoice")

# Access audio and transcription
for sample in dataset['train']:
    audio = sample['audio']
    text = sample['transcription']
    # Use for training ASR models

License

MIT License - See LICENSE file for details.

Citation

If you use this dataset, please cite:

@dataset{parsvoice2025,
  title={ParsVoice: A High-Quality Persian Speech Recognition Dataset},
  author={Mohammad Ranjbar},
  year={2025},
  url={https://huggingface.co/datasets/MohammadJRanjbar/ParsVoice}
}

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