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Czech Speech Combined Dataset
Quality-filtered Czech speech dataset for TTS/ASR training. 146,153 clips across ~1,700 speakers from 5 sources.
Sources
| Source | Clips | Hours | Speakers | Origin |
|---|---|---|---|---|
| audiobooks | 24,535 | ~33h | 13 | Czech audiobook narrations |
| audiobooks_new | 28,131 | ~39h | 8+ | Czech audiobook narrations |
| yodas_czech | 28,208 | ~37h | ~2,300 | YODAS YouTube speech (quality-filtered) |
| voxpopuli_czech | 12,679 | ~33h | 45 | VoxPopuli parliament speech |
| commonvoice_czech | 52,600 | ~67h | many | Mozilla Common Voice |
Quality Pipeline
All audio passed through:
- Duration filter (2-20s)
- SNR analysis (min 10)
- Silence floor check
- Voice activity ratio
- Pacing (chars/sec) check
- Edge cut detection
- Sentence completeness filter (terminal punctuation)
- Whisper large-v3 transcription + confidence filter (YODAS, VoxPopuli)
Audio Format
- 24 kHz mono WAV, 16-bit PCM (embedded in Parquet)
- Columns:
audio(struct with bytes+path),text,source,filename
Usage
from datasets import load_dataset
ds = load_dataset("chosenek/czech-speech-combined", split="train")
print(ds[0]) # {'audio': {...}, 'text': '...', 'source': '...', 'filename': '...'}
# Filter by source
audiobooks = ds.filter(lambda x: x["source"] == "audiobooks")
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