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--- |
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license: cc-by-2.0 |
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task_categories: |
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- automatic-speech-recognition |
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- text-to-speech |
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language: |
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- cs |
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size_categories: |
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- 100K<n<1M |
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--- |
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# ParCzech4Speech (Sentence-Segmented Variant) |
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## Dataset Summary |
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**ParCzech4Speech (Sentence-Segmented Variant)** is a large-scale Czech speech dataset based on parliamentary recordings and official transcripts. |
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This sentence-segmented variant is designed for speech recognition and synthesis tasks, offering clean audio-text alignment and reliable segment boundaries. |
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It is derived from the [**ParCzech 4.0**](https://lindat.mff.cuni.cz/repository/xmlui/handle/11234/1-5360) corpus and [**AudioPSP 24.01**](https://lindat.mff.cuni.cz/repository/xmlui/handle/11234/1-5404) audio collection. |
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Using WhisperX and Wav2Vec 2.0 for automatic alignment, this dataset ensures high-quality segments and provides rich metadata for filtering and quality control. |
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The dataset is released under a permissive **CC-BY**, allowing unrestricted commercial and academic use. |
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## 🔔 Note |
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📢 A **larger unsegmented variant** of this dataset is now available! The unsegmented version provides **longer, continuous speech segments** that do **not follow sentence boundaries**, making it especially suitable for streaming ASR. You can find it under [ParCzech4Speech (Unsegmented Variant)](https://huggingface.co/datasets/ufal/parczech4speech-unsegmented) on Hugging Face. |
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## Data Splits |
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| Split | Segments | Hours | Speakers | |
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|-------|----------|-------|----------| |
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| Train | 682,254 | 1131 | 525 | |
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| Dev | 5,094 | 10.14 | 29 | |
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| Test | 11,379 | 20.63 | 30 | |
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## Dataset Structure |
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Each row corresponds to a sentence-level audio segment with accompanying metadata: |
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| Column | Description | |
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|--------|-------------| |
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| `true_text` | Official transcript from parliamentary stenographic records (unnormalized). | |
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| `rec_text` | Automatically recognized transcript using Whisper model. | |
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| `speaker` | Speaker identifier in the format `NameSurname.YearOfBirth`. | |
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| `dur` | Duration of the segment in seconds. | |
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| `vert` | Vertical file name from ParCzech 4.0 for backward compatibility. | |
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| `n_numbers` | Number of number tokens detected in `true_text`. | |
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| `n_true_words` | Number of true words in the segment. | |
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| `seg_edit_dist` | Levenshtein distance between `true_text` and `rec_text`. | |
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| `align_edit_dist_max` | Maximum word-level edit distance between aligned word pairs. | |
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| `true_char_avg_dur` | Average duration per character in `true_text` (ignoring whitespace). | |
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| `start_token_id` | Start token index (from vertical data) indicating the original source of the segment. | |
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| `end_token_id` | End token index (from vertical data). | |
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| `wav2vec_rec` | Transcript from Wav2Vec 2.0 model with greedy decoding strategy used as a secondary ASR reference. | |
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| `wav2vec_rec_edit_dist` | Normalized edit distance between `wav2vec_rec` and `rec_text`. | |
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| `speaker_text_cnt` | Frequency count of the given speaker-text pair, can be used for deduplication. | |
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## Citation |
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Please cite the dataset as follows: |
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```bibtex |
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TODO |
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``` |
