ParCzech4Speech: A New Speech Corpus Derived from Czech Parliamentary Data
This provides a new, large-scale speech dataset for Czech language modeling tasks, but it is incremental as it builds upon existing parliamentary data with enhanced processing.
The authors tackled the problem of limited speech data for Czech by creating ParCzech4Speech 1.0, a processed corpus derived from Czech parliamentary recordings, resulting in the largest variant containing 2,695 hours with improved alignment reliability over previous versions.
We introduce ParCzech4Speech 1.0, a processed version of the ParCzech 4.0 corpus, targeted at speech modeling tasks with the largest variant containing 2,695 hours. We combined the sound recordings of the Czech parliamentary speeches with the official transcripts. The recordings were processed with WhisperX and Wav2Vec 2.0 to extract automated audio-text alignment. Our processing pipeline improves upon the ParCzech 3.0 speech recognition version by extracting more data with higher alignment reliability. The dataset is offered in three flexible variants: (1) sentence-segmented for automatic speech recognition and speech synthesis tasks with clean boundaries, (2) unsegmented preserving original utterance flow across sentences, and (3) a raw-alignment for further custom refinement for other possible tasks. All variants maintain the original metadata and are released under a permissive CC-BY license. The dataset is available in the LINDAT repository, with the sentence-segmented and unsegmented variants additionally available on Hugging Face.