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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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- 1M<n<10M |
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--- |
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# ParCzech4Speech (Unsegmented Variant) |
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## Dataset Summary |
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**ParCzech4Speech (Unsegmented Variant)** is a large-scale Czech speech dataset derived from parliamentary recordings and official transcripts. |
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This variant captures **continuous speech segments** without enforcing sentence boundaries, making it well-suited for real-world streaming ASR scenarios |
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and speech modeling tasks that benefit from natural discourse flow. |
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The dataset is created using a combination of WhisperX and Wav2Vec 2.0 models for robust automatic alignment and filtering. |
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Segments are formed by aggregating consecutive well-aligned words until encountering a speaker change or misalignment. |
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The dataset is derived from the [**ParCzech 4.0**](https://lindat.mff.cuni.cz/repository/xmlui/handle/11234/1-5360) corpus (official transcripts of parliamentary sessions) and the corresponding [**AudioPSP 24.01**](https://lindat.mff.cuni.cz/repository/xmlui/handle/11234/1-5404) audios. |
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This dataset includes rich metadata and is released under the permissive **CC-BY**, allowing for commercial and academic use. |
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## 🚨 Disclaimer |
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⚠️ **Note:** The current release of this dataset is **partial** (~80%) and **does not yet include the full set of segments**. |
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The **complete version** containing all aligned segments will be made available **soon**. |
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All summary statistics shown below (e.g. total segment count, duration) are **computed on the complete dataset**, **not** the currently available subset. |
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## 🔔 Note |
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📢 A **sentence-segmented variant** is also available [ParCzech4Speech (Sentence-Segmented Variant)](https://huggingface.co/datasets/ufal/parczech4speech-segmented), optimized for tasks requiring clean sentence boundaries and stricter control over segment quality. |
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## Data Splits |
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| Split | Segments | Hours | Speakers | |
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|-------|----------|-------|----------| |
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| Train | 1,311,027 | 2631 | 527 | |
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| Dev | 20,352 | 43.43 | 30 | |
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| Test | 9,127 | 21.37 | 30 | |
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## Dataset Structure |
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Each row represents a continuous speech segment with rich metadata: |
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| Column | Description | |
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|--------|-------------| |
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| `true_text` | Official transcript (normalized, lowercased, punctuation removed). | |
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| `rec_text` | Whisper-based ASR output. | |
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| `speaker` | Speaker ID in the format `Name.DateOfBirth`. | |
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| `dur` | Duration of the segment in seconds. | |
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| `vert` | Name of the vertical file from ParCzech 4.0. | |
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| `n_numbers` | Number of numeric tokens in `true_text`. | |
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| `n_true_words` | Number of words in the segment. | |
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| `seg_edit_dist` | Normalized Levenshtein distance between `true_text` and `rec_text`. | |
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| `align_edit_dist_max` | Maximum edit distance among aligned word pairs. | |
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| `true_char_avg_dur` | **Average per-character duration**, computed at the word level (range 0.035–1.0s/char). | |
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| `start_token_id` | Starting token ID from the vertical format. | |
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| `end_token_id` | Ending token ID. | |
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| `wav2vec_rec` | Wav2Vec 2.0 decoded transcript used for verification. | |
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| `wav2vec_rec_edit_dist` | Normalized edit distance between `wav2vec_rec` and `rec_text`. | |
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## Citation |
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Please cite the dataset as follows: |
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``` |
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TODO |
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``` |
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