metadata

license: cc-by-2.0
task_categories:
  - automatic-speech-recognition
  - text-to-speech
language:
  - cs
size_categories:
  - 1M<n<10M

ParCzech4Speech (Unsegmented Variant)

Dataset Summary

ParCzech4Speech (Unsegmented Variant) is a large-scale Czech speech dataset derived from parliamentary recordings and official transcripts. This variant captures continuous speech segments without enforcing sentence boundaries, making it well-suited for real-world streaming ASR scenarios and speech modeling tasks that benefit from natural discourse flow.

The dataset is created using a combination of WhisperX and Wav2Vec 2.0 models for robust automatic alignment and filtering. Segments are formed by aggregating consecutive well-aligned words until encountering a speaker change or misalignment.

The dataset is derived from the ParCzech 4.0 corpus (official transcripts of parliamentary sessions) and the corresponding AudioPSP 24.01 audios.

This dataset includes rich metadata and is released under the permissive CC-BY, allowing for commercial and academic use.

🔔 Note

📢 A sentence-segmented variant is also available ParCzech4Speech (Sentence-Segmented Variant), optimized for tasks requiring clean sentence boundaries and stricter control over segment quality.

Data Splits

Split	Segments	Hours	Speakers
Train	1,311,027	2631	527
Dev	20,352	43.43	30
Test	9,127	21.37	30

Dataset Structure

Each row represents a continuous speech segment with rich metadata:

Column	Description
`true_text`	Unnormalized official transcript.
`rec_text`	Whisper-based ASR output.
`speaker`	Speaker ID in the format `Name.DateOfBirth`.
`dur`	Duration of the segment in seconds.
`vert`	Name of the vertical file from ParCzech 4.0.
`n_numbers`	Number of numeric tokens in `true_text`.
`n_true_words`	Number of words in the segment.
`seg_edit_dist`	Levenshtein distance between `true_text` and `rec_text`.
`align_edit_dist_max`	Maximum edit distance among aligned word pairs.
`true_char_avg_dur`	Average per-character duration, computed at the word level.
`start_token_id`	Starting token ID from the vertical format.
`end_token_id`	Ending token ID.
`wav2vec_rec`	Wav2Vec 2.0 decoded transcript used for verification.
`wav2vec_rec_edit_dist`	Normalized edit distance between `wav2vec_rec` and `rec_text`.

Available Versions

v1.0-full – Full dataset release with all intended data included. (Latest)
v0.1-partial – Initial partial upload containing a subset of the training data. Kept for backward compatibility only. Users should prefer the full version.

By default, load_dataset() will download the latest version.
To explicitly load a specific version, you can specify the revision parameter:

from datasets import load_dataset

# Load a specific version of the dataset
dataset = load_dataset("ufal/parczech4speech-unsegmented", revision="v0.1-partial")  # or "v1.0-full"

Citation

Please cite the dataset as follows:

TODO